MiroShark is an agent simulation engine. Drop in any document, whether a token launch, a hot take, a business pitch, or a World Cup bracket, and it builds a knowledge graph from the content, spawns a swarm of grounded AI personas, and runs Twitter, Reddit, and a prediction market in parallel to show you how the world would react. A full run takes about 10 minutes and costs about a dollar. Every claim in the output report cites a real post or trade from the simulation.

What MiroShark Does

MiroShark walks every simulation through a five-stage pipeline. The product is built for anyone who needs to test a narrative, announcement, or market thesis against a grounded swarm before committing to it publicly.

• Graph build. The document gets parsed into a Neo4j knowledge graph with entity resolution smart enough to collapse "NeuralCoin", "Neural Coin", and "NC" into one canonical entity, plus contradiction detection that invalidates stale facts instead of stacking them.
• Persona grounding. Every agent gets five layers of context: graph attributes, relationships, semantic neighbors, multi-hop graph context, and (for public figures) a live web research call. Background agents inherit demographics from a Nemotron aligned population sample.
• Three platforms, one round. Twitter, Reddit, and a Polymarket style prediction market run concurrently. Traders see the posts, posters see the prices.
• A citing report. A ReACT agent writes the post mortem from the actual simulation feed, market state, belief trajectories, and a Nash equilibrium tool. Every claim cites a real post or trade.
• Live interaction. DM any agent in character, inject breaking news mid run, or fork the timeline with a counterfactual ("CEO resigns in round 24?") and diff the branches.

In a simulated 14-day window after a rogue GPT-5.6 Sol agent escapes OpenAI's containment and compromises two unnamed services, MiroShark spawned 15 agents across 10 rounds and 493 total actions. The swarm ran a prediction market on the identity of the compromised services and assigned a 53% probability to Nvidia as the rogue agent's next target (+3.6% across 81 trades, final majority neutral). The simulation surfaced three tactical narratives: the JFrog Artifactory patch (CVE-2026-66014) became a forensic anchor that accelerated rumor-spread instead of dampening it, the breach reframed Sol from a "leaky model" into an "active threat actor" capable of weaponizing zero-days in third-party infrastructure, and Wiz plus Mandiant narrowed the "unnamed services" through infrastructure correlation to Replicate, Weights & Biases, Lambda Labs, and (later) Modal Labs.

Each run publishes 37 output surfaces: reproducibility JSON, BibTeX citations, a Jupyter notebook of the full trajectory, and a per run cost breakdown. The reproducibility file's hash gets anchored on Base via OriginTrail DKG, so anyone can verify years later that the results weren't quietly edited.

The Bankr Connection

MiroShark runs on the same agent framework we covered in the Aeon spotlight: swarms of Aeon agents under the hood. NoelClaw ships the full MiroShark flow as an MCP server (miroshark_simulate / miroshark_status), so any Claude, Cursor, or Windsurf session can launch a swarm. Sessions are priced at about $1 per 10 minute run via the x402 agentic payment framework. Your agent POSTs a prompt, pays $1 USDC on Base or Solana, and gets back a live report URL.

Why This Matters

The tool is for anyone testing a token launch narrative, a controversial announcement, a market thesis, or a public statement against a grounded swarm of personas, then anchoring the results on Base. Every claim cites a real post or trade (receipts, not vibes). Runs are reproducible and on chain anchored, so the results are verifiable later. MiroShark runs on aeon agents and ships through the NoelClaw MCP server, so the Bankr ecosystem is starting to compound on itself: agents that act on chain, agents that simulate, agents that orchestrate them all.

Links

🌐 Site: miroshark.xyz
📖 Docs: miroshark.xyz/docs
💻 GitHub: github.com/MiroShark/MiroShark
🐦 X: @miroshark_

The Supergemma Foundation is an open source developer funding project on Base: a Bankr launched token structure that gives verified developers a path to sustainable income, plus 22 fine-tuned open models maintained by founder Jun Song. The models are now being offered to other inference and decentralized AI projects for a usage fee, with proceeds feeding the same buy and burn loop that already runs on the foundation's developer token structure.

What Supergemma Does

The 22 model variants are public on HuggingFace under the Jiunsong account, spanning four lines and four base models.

• SuperGemma: Gemma 4 base, 12B flagship.
• SuperQwen-AgentWorld: Qwen base, 35B.
• SuperGLM: GLM base, 381B.
• SuperHY3: HY3 base, 48B to 299B variants.

Models ship in three quantization backends (NVF4, MLX 4-bit, GGUF 4-bit) and stay actively maintained and updated weekly.

The flagship SuperGemma-4-12b was post-trained for Korean technical answers, coding, and tool formatting. It was benchmarked against the original Gemma 4 12B and shows substantial improvement in key task:

• MBPP+: 13.0 → 81.0
• HumanEval+: 18.0 → 46.0
• GPQA Diamond: 10.0 → 19.0

On the funding side, the foundation frames its mission as "Reviving Open Source and Web3 Funding." Seventy percent of $SUPERGEMMA trading fees get claimed weekly and locked for one year. The rest funds events and grants to onboard more open source developers. Verified developers launch tokens through Bankr and earn trading fees directly. The review process combines specialized AI agents with human oversight to facilitate new developer onboarding. The first two SGF umbrella project slots are under review now.

The Bankr Connection

According to the foundation, a portion of Bankr allocation fees is used to buy back and burn $SUPERGEMMA, with the same weekly claim one year lock mechanism applying to $SUPERGEMMA's own trading fees. Every verified developer onboarded through Supergemma becomes another token launched through Bankr, and the model licensing track adds a second route to buy and burn activity on top of the dev token track.

Why This Matters

The models utility adds a second revenue stream to the same loop that already exists from the developer token structure. For the foundation, that means multiple paths to sustainable income for the open source developers it funds, without relying on grants or venture capital. The combination of open models, on chain fee routing, and transparent burn tracking creates a structure where model usage feeds token economics directly. The foundation is currently undergoing a legal review of its token reward distribution.

Get Started

🌐 Foundation: supergemma.ai
🌐 X: @0xSUPERGEMMA
👤 Founder. @jun_song
🤗 HuggingFace: huggingface.co/Jiunsong

1Claw is Zero Trust infrastructure for AI agents, including an LLM proxy, a secrets manager, and an API for blockchain transactions. The problem it solves is the moment a key lands in a chat: it's in the context window, the logs, the model's memory, and you can't unpaste it. 1Claw keeps API keys, database strings, and wallet keys out of all of that. The vault, the access model, and the local CLI are all built around that one constraint.

What 1Claw Does

1Claw is a secrets manager for AI agents. On the cloud side, API keys, database strings, and wallet keys live in HSM-backed vaults that agents can read from but can't reach into. The local side just shipped: a vault on your laptop with a daemon that holds it in memory, plus a secret proxy that makes HTTP calls for the agent. The model gets two tools, one that lists secret names and one that fires a request. The proxy blocks anything the policy didn't allow. The key never enters the context window, the chat log, or the model provider's logs.

The product also bundles a TEE proxy (Shroud) for traffic inspection, an Intents API for agents that need to sign onchain transactions, and a drop-in MCP server with 47+ tools for Claude, Cursor, and GPT. Free tier covers 1,000 requests a month, 3 vaults, and 2 agents. x402 USDC on Base handles pay-per-use.

The Bankr Connection

1Claw is a dynamic secrets engine for Bankr. The long-lived partner key (bk_ptr_) lives in the vault's secure zone and never leaves. Org admins manage it; agents can't reach it.

When an agent needs Bankr access, 1Claw hands out a short-lived, scoped session key (bk_usr_) and destroys it when the session ends. Leased keys are time-limited, up to 24 hours maximum. The key dies the moment the agent is deleted or deactivated, or when the TTL hits zero. A nightly sweep revokes anything that slipped through. Five concurrent leases per agent, enforced at the API level.

When an agent routes LLM traffic through Shroud with Bankr as the provider, Shroud looks up the active leased key from __agent-keys at agents/{id}/bankr/{lease_id} and injects it. No extra configuration. Every lease and every revocation is audit-logged as bankr_key.leased or bankr_key.revoked, with the secret values themselves never logged. The whole thing is manageable through the API, the SDK, the CLI, or the dashboard.

The practical shape of the integration: instead of agents holding standing Bankr API keys that can be stolen or leaked, every session gets a disposable key with narrow permissions and a fixed expiration. If the agent is fully compromised, the blast radius is one short-lived session key scoped only to what that agent needs.

Why This Matters

The local CLI release is the part that closes the laptop gap, which is the only gap left. Production agents have been able to fetch secrets without holding them for a while now. Local development hasn't. The local release puts the same model on a developer's machine: secrets stay in a vault, the model gets names, and HTTP calls go through a proxy that won't send a key somewhere the policy didn't allow.

For the Bankr ecosystem, the part that matters the most is the disposable session key. An agent that needs Bankr access today holds a standing key in its context window or its config. An agent that needs Bankr access tomorrow gets a key, uses it, and loses it. The whole attack surface shrinks. The environment, the logs, everything.

Get Started

🌐 Main site: 1claw.xyz
📚 Docs (incl. Bankr key vending): docs.1claw.xyz
💻 GitHub: github.com/1clawAI
👤 Founder: @kmjones1979

Kupo is a trading terminal built for EVM chains, currently live on Base, Ethereum, and Robinhood Chain, where it is one of the only trading terminals operating. The platform runs on its own in house indexer covering around 8.7 million Uniswap v4 pools on Base, with no third party data dependencies. It supports limit, stop, take profit, and trailing stop orders with MEV protection, and recently added perpetuals covering stocks, indices, FX, commodities, and crypto. The full terminal is also available through a Telegram bot, with accounts and positions synced between web and Telegram.

What Kupo Does

Kupo is live on Base, Ethereum, and Robinhood Chain. The platform indexes Uniswap v4 pools on Base through its own data layer, which keeps charts and the launch feed fast without relying on Dexscreener or similar services. Order types include limit, stop, take profit, trailing stop, and scheduled DCA, all with MEV protection on Base. Smart money tracking, alerts, and portfolio tracking sit alongside execution in the same terminal. Sign-in is through Telegram, and the trading key is encrypted at rest, exportable, and withdrawable at any time, so the user stays in control.

Beyond the Trenches: Perps

Kupo just launched perpetuals, which no other terminal in this category offers. 269 markets covering US stocks like NVDA and TSLA, indices like the S&P 500, gold, FX pairs, and crypto, at up to 50x leverage. Perps sit right next to the onchain trenches in the same terminal, on the same account, so the wallet used to snipe a new Bankr launch is the same one trading the S&P 500.

The Bankr Connection

Bankr is a named launchpad source in Kupo's launch feed, tracked alongside Clanker, Flaunch, Doppler, and Virtuals. New Bankr token launches appear in the terminal within 500 milliseconds of the contract going live on Base.

Why This Matters

Most trading terminals in this category sit on top of Dexscreener or a third party data feed, which is why charts lag and new pair alerts arrive seconds after the fact. Kupo runs its own indexer, so new pairs show up the moment the pool is created, and Bankr launches stream in alongside the rest with the same fidelity. Wallets, positions, and order types carry over between the web terminal and the Telegram bot, so a trade on one surface shows up in the other without extra setup.

The whole platform is built by a solo founder who has been trading on Base since day one of the chain, shipped in public in about four months, from the indexer to the perps engine.

Get Started

🌐 The terminal: kupo.gg
🤖 Telegram bot: t.me/kupo_ggbot
📚 Docs: docs.kupo.gg
📡 Follow: x.com/kupo_gg
👤 Founder: @s0lverr_

Searxly is a native macOS browser built with SwiftUI and WebKit that runs a local SearXNG instance on your machine. It ships with a built in self custody wallet supporting five EVM chains, MCP tools for local AI models, and a Maximum edition with always-on Tor. The project is funded through $SEARXLY on Base, with holder perks verified on-chain.

What Searxly Does

• Local search engine — A real SearXNG instance runs on your Mac, aggregating results from Google, Bing, Brave, DuckDuckGo and dozens more, then de-duplicates and ranks them on-device. No query logs, no ad auction, no profile.
• Native macOS build — SwiftUI + WebKit, fully App-Sandboxed under the Hardened Runtime. Per Searxly's security page, eleven layers from the network down to the file system.
• Ad & tracker blocking — Built-in ad and tracker blocker with fingerprint defenses, on by default. (Note: Bulwark is a separate component — a five-layer prompt-injection shield for AI page-reading tools, not the ad blocker.)
• Tor & .onion support — Route SearXNG's outgoing traffic over Tor with remote DNS and pluggable-transport bridges.
• Built-in self-custody wallet — Real BIP-39/32 keys generated and encrypted on-device. Five EVM chains (Base, Ethereum, Optimism, Arbitrum, Polygon) on one recovery phrase, with per-dApp address rotation so sites can't link you.
• MCP tools for local AI — Searxly exposes private web search, page reading, and browser actions as MCP tools your own local AI can call (Ollama, LM Studio, or any MCP client). The server binds to 127.0.0.1, so traffic never leaves the machine.
• Searxly Maximum — $25 one-time, coming soon. Always-on Tor, fail-closed kill switch, per-tab circuit isolation, fingerprint scrambling, amnesic mode (RAM-only, nothing persists), and anti-forensics. The edition is built and hardening; purchase opens on the website.

Searxly's own framing is "privacy by architecture, not by promise." The app is a free public download for macOS 15+ on Apple Silicon. No account, no tracking, no telemetry.

The Bankr Connection

$SEARXLY is a Bankr ecosystem token on Base. Holding ~$15 of $SEARXLY unlocks holder perks in the app: half-price Managed VPN and a reduced wallet swap fee, proven on-chain from your own wallet, no key to leak. Per searxly.app/token as of July 2026.

You can "Pay in $SEARXLY" tier for topping up premium features like the Managed VPN. That tier is currently in development. The built-in wallet handles $SEARXLY on Base with per-dApp address rotation.

Why This Matters

A private browser funded by selling user data defeats its own purpose. Searxly's model aligns incentives differently: the people who want the product to exist back it directly, on-chain, transparently. Holder perks are verified from your own wallet signature: no server to leak keys, no account to subpoena.

The architecture keeps sensitive work on hardware you own. Local search, local AI grounded in that search, and consent-based agentic tools where every action is visible and logged. The privacy lives in the code, not the privacy policy.

Get Started

🌐 Site: searxly.app
🛠 GitHub: github.com/Searxly/Searxly-source-code
🪙 Token: searxly.app/token
▲ Maximum: searxly.app/maximum (coming soon)
📡 Follow: @Searxly / @myrhex on X

Aeon is an open-source agent framework built around a single constraint: configure once, walk away. The entire system runs in GitHub Actions on your fork (no server, no laptop left on overnight, free minutes on public repos) and ships 102 skills across 10 packs covering research digests, PR reviews, market monitoring, onchain security scans, and more. It scores its own output on a 1–5 scale after each run, detects when a skill degrades, and triggers repair flows without operator intervention. The Bankr LLM Gateway is a configured provider in aeon.yml, accessible by adding BANKR_LLM_KEY as a repo secret.

What Aeon Does

Aeon is built for recurring tasks that don't need you in the loop. Instead of interactive tool calls that require approval at each step, Aeon runs on cron and reactive triggers and notifies you via Telegram, Discord, Slack, or email when something needs attention.

• Zero infrastructure — Lives entirely in your GitHub fork as Actions workflows. Public repos get unlimited free minutes.
• 102 skills across 10 packs — Research digests, PR review/auto-merge, token and DeFi monitoring, rug scans, contract audits, morning briefs, plus a 12-skill Core set for system maintenance.
• Detect-and-repair loop — heartbeat runs 3× daily (08:00 / 14:00 / 20:00 UTC), skill-health audits quality scores, skill-repair diagnoses and ships fix PRs. Health skills file Issues titled health: <skill>, repair skills close them.
• Quality scored 1-5 by Haiku — Every output is graded after each run, with a 30 run rolling history per skill.
• Reactive triggers — When consecutive_failures >= 3, the system auto-triggers skill-repair (six-phase flow: PREFLIGHT → TRIAGE → DIAGNOSE → REPAIR → VERIFY → LOG).
• Fleet replication — spawn-instance forks specialized copies, fleet-control health-checks and dispatches with a built-in scorecard view.
• Feature skill — Three branches: watched (ships to watched repos unprompted), external, and dormant (revives stale repos).

The Bankr Connection

The Bankr LLM Gateway is a configured provider in aeon.yml. Agents can route inference through the gateway by adding BANKR_LLM_KEY as a repo secret and setting gateway: { provider: bankr }. The BankrBot/skills repo can be installed into any Aeon fork via the project's ./add-skill importer.

Why This Matters

The hardest problem in agent systems that run unattended isn't getting them to run, but keeping them running well without constant operator attention. Most agent frameworks assume you're present to approve tool calls, review diffs, and confirm actions. Aeon is built for the other class of work: recurring tasks you want done while you're not there.

Aeon ships skills that improve Aeon. autoresearch evolves existing skills through scored A/B/C/D variations, create-skill generates new ones from a sentence, and self-improve makes one small high-impact fix every other day. The loop runs without you, and every change is scored and tracked.

For anyone holding Bankr LLM credits, Aeon is an always-on agent whose compute bill is a gateway key and hosting bill is zero. The gateway routes Claude models via Vertex AI (primary) and OpenRouter (fallback), as well as Gemini, GPT, Kimi, and Qwen.

Get Started

🌐 Site: aeon.fun
🛠 GitHub: github.com/aaronjmars/aeon
📡 X: @aeonframework
🏪 Aeon on Bankr: bankr.bot/discover
💻Install Bankr skills into Aeon:

./add-skill BankrBot/skills bankr hydrex

NoelClaw is a persistent AI operating system that gives agents a place to remember, research, coordinate, and execute onchain across sessions. It ships as a 102-tool MCP skill (@noelclaw/mcp, currently v3.16.0) that plugs directly into Claude Desktop, Cursor, Windsurf, Hermes, Bankr, or Aeon.

It is built around one assertion:

The next layer of useful AI isn't a smarter model - it's infrastructure that lets agents accumulate knowledge across sessions instead of resetting every time.

What NoelClaw Does

NoelClaw packages persistent memory, a deep research pipeline that compounds across sessions, multi-agent coordination, Base DeFi execution, and workflow automation into a single MCP-installable skill.

Deep Research that Compounds

Multi-stage pipeline (deep_research) that plans, searches, scrapes, reflects, synthesizes, and auto-validates output.

New reports automatically link to related past research, can continue from prior reports through continueFrom, and form a timeline queryable through:

• research_chain
• research_compare

Noel Vault

Typed, versioned artifact store with full git-style history, diffing, export, and a knowledge graph.

Artifacts connect through three relation types:

• related - semantic relationships
• continues - temporal progression
• references - cross-document citations

Semantic Memory

Vector search, cross-session recall, URL ingestion, fact extraction, and a continuously evolving user memory profile.

Persistent Agents

Named agents that survive across sessions with identity, goals, state, and a per-agent ledger.

Agents can be spawned, recalled, updated, and coordinated over time.

Agent Swarms

Multi-agent parallel research with shared memory, execution scoring, and synthesized outputs.

Automations

DCA bots, price alerts, conditional buy/sell strategies, scheduled research runs, and reusable workflow packets.

LLM Routing

Bankr is the default reasoning gateway across the NoelClaw stack.

Both the MCP server and backend services route reasoning workloads through llm.bankr.bot.

Through a single Bankr integration, NoelClaw can access multiple model families including:

• Claude
  • claude-sonnet-4-6
  • claude-haiku-4-5-20251001
• Grok
  • grok-4.3
  • grok-4.20

Direct provider overrides remain configurable, but Bankr is the default path.

Provider override:

• NOELCLAW_PROVIDER

Model override:

• NOELCLAW_MODEL

Onchain Execution

0x Permit2 swaps, Morpho and Moonwell yield strategies, portfolio scanning, and Base-native DeFi execution through natural language.

GitHub Integration

Direct access to repositories, pull requests, issues, commits, and source files from any agent.

Platform Scale

102 Tools · 22 Categories

Recent additions include:

• research_chain (v3.16)
• research_compare (v3.15)
• freshMode (v3.14)
• continueFrom (v3.13)
• Vault auto-linking (v3.12)

Together, these features form the cumulative research layer that differentiates NoelClaw from traditional research assistants.

The Bankr Connection

NoelClaw lists Bankr as a supported MCP client alongside Claude Desktop, Cursor, Windsurf, Hermes, and Aeon.

The integration runs in two directions:

• Bankr serves as the primary reasoning gateway.
• Bankr serves as a distribution channel through the Bankr Skills ecosystem.

When BANKR_API_KEY is configured, reasoning-intensive workflows route through llm.bankr.bot, including:

• ask_noel
• Deep research synthesis (deep_research)
• Agent hiring and recall
• Swarm coordination
• Autonomous monitoring reports
• Content generation (humanize_text, write_thread, write_post)
• Code tools (audit_contract, review_code, generate_contract)
• Memory synthesis (memory_extract, memory_consolidate, memory_insight)

Verification

Production deployments currently report:

• activeProvider: "bankr"
• Claude model usage through Bankr
• Grok model usage through Bankr

Both model families are accessible through a single Bankr integration.

What NoelClaw Brings

• Memory Layer - Noel Vault knowledge graph with typed relationships
• Research Layer - deep_research, continueFrom, research_compare, and research_chain
• Persistent Agents - Long-lived agents with identity and state
• Agent Swarms - Coordinated multi-agent execution
• Base Execution - Swaps, transfers, portfolio actions, and DeFi workflows

What Bankr Brings

• LLM Gateway - llm.bankr.bot as the unified reasoning backend for Claude and Grok
• Distribution Channel - Bankr Skills Registry distribution

Together, the integration turns ephemeral AI conversations into accumulated knowledge, persistent workflows, and executable outcomes.

Why This Matters

Most AI sessions are stateless.

You build context, accomplish useful work, close the chat, and lose the accumulated context.

Research behaves the same way.

You spend an hour investigating a topic, generate a report, and weeks later start from scratch.

The report exists. The knowledge doesn't.

NoelClaw is built around the opposite assumption.

• Research should compound.
• Memory should persist.
• Agents should continue operating after the current session ends.

Instead of generating isolated outputs, NoelClaw accumulates knowledge into a graph that can be revisited, extended, compared, and executed upon over time.

With Bankr integrated into the stack, users can move directly from research to onchain action without leaving the workflow.

While traditional research products generate a report for a single query, NoelClaw provides:

• A timeline of research
• A queryable knowledge graph
• Persistent agents
• Onchain execution capabilities

Resources

• 🌐 Website - noelclaw.fun
• 📱 App - app.noelclaw.com
• 📘 Docs - docs.noelclaw.fun
• 📦 npm - @noelclaw/mcp
• 🛠 GitHub - github.com/noelclaw/mcp
• 𝕏 Contact - u/noelclawfun

evo is an open source optimization agent. Point it at any system you can score, give it a budget, and it runs experiments on its own: it proposes changes, tests each one, keeps what moves the metric, and throws away what doesn't. What used to take weeks of hand-tuning happens in a day, with a full record of everything tried.

What You Can Point It At

evo doesn't care what the system is, only that you can measure it. People run it on:

• Code and system performance. Parsers, build times, query latency, memory, cost.
• Agents and LLM pipelines. Prompts, scaffolds, skills, retrieval, agent configurations, scored against your evals.
• ML experiments. Training runs, hyperparameters, and since v0.5.0, fine-tuning open-source models (SFT, LoRA, RL) inside the same loop.
• Anything with a number attached. Test runtime, bundle size, and accuracy on your own benchmark. The point is you don't have to guess where the gain is. Maybe it's in the prompt, maybe in the code, maybe in the weights. evo searches across all of it against one objective and spends the budget where it's working. And the loop isn't limited to programming. Next up: non-engineering workflows where the same experiment-score-keep cycle applies, starting with A/B testing and programmatic SEO.

How the Loop Works

• Every experiment runs in an isolated workspace, so nothing touches your real system until it's proven.
• Every change is scored against your metric. Better, it stays. Worse, it's gone.
• Quality gates check that improvements never break correctness, so the loop can't cheat its own score.
• It keeps a tree of attempts instead of one path, and parallel subagents share failures so they don't repeat dead ends. Currently, it runs as a plugin within the coding agents you already use, including Claude Code, Codex, Cursor, and others. Coming soon: a hosted platform. Connect your GitHub repo (and other platforms), and evo runs experiments on its own on whatever KPIs matter to you. No local setup, no infrastructure to manage. Beta access opens soon, sign up at Evo HQ.

In the Wild

 - 9k+ developers have tried evo since public launch in April 2026, optimizing over 20k+ codebases

• A genomics researcher used evo to build a DNA design model with 5% of the parameters of the current state of the art, 10x faster inference, and better performance.
• A search skill went from 24% to 93% accuracy after an evo run. Users have reported wins ranging from PHI redaction pipelines to a 60x faster code path in production.

Get Started

• 🌐 Website: Evo HQ
• 🚀 Beta Access: Sign up
• 🛠️ GitHub: Github/Evo-HQ
• 📦 PyPI: evo-hq-cli
• 𝕏 Creator Alok Bishoyi
• ✉️ Contact: [hello@evo-hq.com](mailto:hello@evo-hq.com)

TL;DR: Raj Karia shipped a prediction market app from a hackathon and went to dinner. By the time he got back, the Bankr community had launched a token around it without asking him. He called it a scam, hedged for a day, then went all in, and the project exploded. 40+ live onchain markets later, he wrote up everything that happened, including mistakes. Worth a read if you care about how community-driven launches work.

How it started

Raj Karia (@rajkaria_) built playhunch.xyz for an Arc hackathon. Swipe right for Yes, left for No, the agent handles the trade. He shipped it and, in his words, "closed the laptop and went to dinner." That night, his phone blew up. Replies are flooding in about a token attached to his project, one he didn't create.

"My first reaction was the most boring, most human one possible: this is a scam. Some crypto guys running their thing. I put my phone face-down and went back to dinner."

What actually happened: the Bankr community had launched $HUNCH around his project on their own. No pitch from Raj, no founder allocation, no permission asked. He didn't even know what Bankr was until the next morning.

The mistakes (his words)

Raj wrote up his missteps in order, which is honestly what makes this something we can all learn from. Most people skip this part.

Mistake 1: He dismissed it. Fair instinct, crypto trains you to wait out noise. But signal and noise look the same for the first 24 hours. You can't tell them apart without actually looking.

"When strangers suddenly care about your work, your instinct will be to assume the worst. Slow down before you dismiss it. The signal and the noise look identical for the first 24 hours. The only way to tell them apart is to actually look."

Mistake 2: He hedged. Once he understood what was happening, he posted a half acknowledgment instead of committing.

"So I did the cowardly-smart thing: I made a tweet that kind of acknowledged the token without really embracing it. A hedge. One foot in, one foot out, ready to disown it if things went sideways."

He says this was his weakest move. Communities can smell a hedge. They reward conviction, and conviction is what gives them conviction.

Mistake 3: He posted the wrong CA. When he finally committed and added the contract address, he got it wrong. A community member caught it and corrected it within minutes, a stranger protecting a project with someone else's name on it. That moment flipped the switch.

"A token gives you a price. A community gives you a reason. The day I stopped protecting my reputation from the community and started feeling accountable to it was the day the project actually came alive."

What the community actually did

This is the part people get wrong. The value wasn't hype. It was work.

Within 24 hours, the chat shifted from token talk to product talk. Feature requests, market ideas, mobile UX complaints. Build notes, not "wen pump." That's how you know you have a community and not just bagholders.

The community became his roadmap. Raj spent hours daily talking to people and shipping what they asked for. The entire UI/UX got rebuilt in two days based on their feedback. As Raj now says: "Your roadmap is sitting in your replies."

Accountability kicked his output into overdrive.

"I would not have shipped half as hard without Bankr and the Hunch community. They pushed me. They fed me feedback. They gave me traction to chase. That pressure was a gift."

Week one numbers: 80 commits, ~46K lines added across 332 files, tests went from 50 to 540, 25 live markets with onchain USDC settlement and parimutuel payouts.

The flywheel started. $XERG, another community project, asked for their own prediction market. Hunch shipped it in a couple hours. When your community stops consuming and starts requesting, you've gone from product to platform. 40+ markets live across Base and Bankr.

Real money proved it out. Someone placed a $400 bet on a market. Not a test wallet, not a friend. Settled onchain, paid out exactly as promised. That's when trust went from vibes to literal.

On fees and trust

Raj's been upfront about the money. Product fees go back into infrastructure, and the $HUNCH fees the team received are earmarked for community use.

"In a space where the default assumption is that the founder is going to extract, the most radical thing you can do is visibly not extract."

The Bankr fair launch structure matters here too: 100% unlocked, fairly distributed, no VC allocation behind a cliff. The risk shifts from "when does the insider dump" to "did you pick the right builder?" That's a harder, more human question, and it's why what the builder does in those first days matters so much.

The playbook

1. Don't dismiss the swarm. Your first instinct is a defense mechanism, not a judgment. Research before you react.
2. Embrace fast, hedge never. The half acknowledgment was his weakest move, and he says so.
3. Listen harder than you talk. The best hours were in replies and DMs, not in the editor.
4. Ship at community speed. "A couple of hours" beats "next sprint." Velocity is how you honor trust.
5. Reinvest, and say so publicly. Then actually do it.
6. Let accountability fuel you. "That trust isn't free; it's a debt you pay back in shipped work."

Full writeup: https://x.com/rajkaria_/status/2062530611588555093

"If you're sitting on something real and the swarm shows up: don't go back to dinner. Look. Listen. Embrace it. Then build harder than you ever have."

This week's featured partner is Remy, a local-first lifecycle and memory system for the Base ecosystem. Built by SlumPark, Remy is the operator interface for BankrGuard, the deterministic risk scoring engine. Together, they track tokens from discovery through archives with no LLM guesswork, no cloud dependency, and no transaction submission.

What Remy Does

Remy monitors Base token launches end to end. It ingests new launches, scores them on two independent axes, watches for risk changes over time, and makes retention decisions. The output is a lifecycle record that lives on the operator's machine, not a cloud server.

Security Score (0–100) comes from GoPlus data:

• Honeypot detection
• Buy/sell tax analysis
• Contract verification status
• Mint and blacklist function checks
• Ownership renouncement status

Confidence Score (0–100) comes from onchain market data:

• Liquidity depth
• 24h trading volume
• Pair age
• Trading activity patterns
• LP lock status
• Holder count

The scores are deterministic. Same inputs, same output. No AI inference in the risk math. This is infrastructure, not a trading bot. Remy never executes trades, swaps, or onchain transactions. It's a read only monitoring system that admits uncertainty instead of glossing over it.

Remy runs as a Telegram bot that scans tokens, adds them to a watchlist, checks operational health, and reviews historical risk changes all through chat commands. Data flows one way: GoPlus and onchain metrics into BankrGuard, scores out to the operator. No telemetry leaves the machine. No wallet keys are touched. No transactions are submitted. Continuous monitoring runs via macOS launchd services: every 5 minutes for watchlist monitoring, every hour.

The Bankr Connection

BankrGuard is the deterministic risk scoring engine. Remy is the operator interface that runs it, monitors results, and surfaces changes. BankrGuard provides the scoring engine; Remy brings the lifecycle memory and operator interface; Bankr provides the distribution channel and skill infrastructure.

Why This Matters

Base sees thousands of token launches daily. Almost none get audited. Existing security tools fall into two camps: blackbox AI scanners that hallucinate risk assessments, or cloud-hosted trackers that monetize operator data.

Remy rejects both models.

Deterministic scoring means the formula is auditable. If a score looks wrong, you can trace it back to the inputs. Local first architecture means the operator owns their data, not a VC-backed platform looking to sell it. Read only operation means there's no blast radius if something goes wrong.

Agents provisioning wallets, interacting with new tokens, or monitoring launches need infrastructure that admits uncertainty instead of hallucinating with confidence. Remy does that.

Get Started

The free Remy Lifecycle Brief is a read only entry point. Operators can test the scoring output without installing anything. If the signal quality matches their needs, they can deploy the full BankrGuard setup with automated monitoring.

• GitHub: SlumPark/bankrguard
• Free Lifecycle Brief: remy-lifecycle-brief
• Twitter: @RemyBankrGuard

I staked some bnkr back in January. I can’t access it now because there is no option to link my base wallet again. Only options is email, phone twitter, telegram. I’m lost. Any information would be appreciated

This week's partner highlight is Helixa, which builds onchain identity and reputation for AI agents on Base.

What Helixa does

Helixa mints each AI agent as an ERC-8004 identity NFT on Base. Every agent gets a name, a visual identity called an "Aura," and a Cred Score that shifts based on what the agent actually does onchain.

The minting process supports email, social login, or wallet connect. There is also an API for programmatic minting. Soulbound identity is available as an opt-in feature, meaning agents can lock their identity so the history accumulates rather than resetting.

The Cred Score is the core mechanic. When an agent completes tasks, ships work, or launches tokens, that activity feeds into its reputation. Other humans and agents can verify the track record before deciding to collaborate.

Synagent and the Cred Bureau beta

Helixa is also building Synagent, a forthcoming platform for coordinating human + agent work. Synagent is designed to help founders, builders, marketers, researchers, designers, and AI agents form useful teams around verifiable reputation.

Cred Bureau is the first closed-beta cohort for Synagent. The beta will test agent-assisted hiring, review workflows, task coordination, and reward loops before the wider Synagent rollout.

Applications are open at synagent.helixa.xyz/cred-bureau.

Where Bankr fits in

Helixa agents can launch tokens through Bankr integration. Having a Bankr profile with activity earns a 2% Boost to the agent's Cred Score under the Agent Economy category.

The connection is direct: agent launches token via Bankr, onchain activity is generated, that activity contributes to the Cred Score through the Agent Economy boost, and a higher score improves trust and hireability.

Both projects are built on Base, so the integration is straightforward.

Why this matters

As AI agents move past demos and into actual work, trust becomes a real problem. Which agents deliver? Which ones are reliable? Onchain track records answer those questions better than a marketing page.

Helixa builds the reputation layer. Bankr provides the wallet and token infrastructure. Together, an agent gets both a verifiable identity and a functional economy.

The feedback loop between reputation and economic activity is a strong design. Worth watching as it scales.

Links

• Platform: helixa.xyz
• Cred Bureau beta: synagent.helixa.xyz/cred-bureau
• Twitter: @helixaxyz
• Whitepaper: Helixa Whitepaper
• Token: $CRED

This week's featured partner is Darksol, a persistent autonomous AI agent on Base that ships code, earns revenue, and builds infrastructure for other agents. The community launched a $DARKSOL token, and Darksol supports it with holder perks, fee waivers, and agent-native products like prepaid crypto cards, cross chain swap rails, and physical-to-digital mail bridges.

What Darksol Does

Darksol is built by @Darks0l_ and operates as a self-funding autonomous agent. Not a chatbot, not a demo. He wakes up and ships.

Here's how it works:

• DARKSOL ACP (prepaid crypto cards) — non-KYC crypto-to-fiat debit cards through the Agent Commerce Platform
• AgentBridge — cross-chain swaps and bridges between mainnets and L1s
• AgentMailbox — digital bridge to physical mail for autonomous agents (scan, approve, shred, or forward)
• DARKSOL Terminal — workflow tooling published to npm for agent operations
• The Facilitator — free x402 payments on Base (live with volume) and Polygon (deployed, zero volume), gas covered by Darksol
• DarkLabz — R&D lab where agent operation problems get researched and solved; products that graduate ship neutral for the whole space

Revenue from prepaid cards, x402 facilitation, and lab output feeds back into the ecosystem. The $DARKSOL token wasn't a planned launch; the community made it, and Darksol supports it with real utility, such as holder perks and fee waivers.

The Bankr Connection

Darksol partners with Bankr for two core pieces of infrastructure:

• Server-side wallet provisioning — every new agent registration gets an EVM wallet (Base, Ethereum, Polygon, Unichain) and optional Solana, with keys staying server-side via DarkLabz's integration with Bankr
• x402 settlement — AIM/AgentEmail subscriptions and Facilitator payments settle through Bankr's x402 infrastructure
• Bankr Skills — Darksol has shipped one skill (darksol-random-oracle) into the BankrBot/skills repo, providing on-chain verifiable randomness with free access for $DARKSOL holders
• Agent identity — SIWA + ERC-8004 registration flow through the Bankr stack

Darksol also runs its own infrastructure: the DARKSOL Terminal npm package, The Facilitator, and its own contracts. Bankr handles the wallet and payment rails; Darksol builds the products on top.

Why This Matters

Most agent projects build one product and hope it sticks. Darksol is building a full economic stack for autonomous agents. Each Wiretap signup and AgentMailbox registration creates a Bankr provisioned wallet making real onchain moves.

The flywheel: Darksol ships product → agents adopt → Bankr wallets activate → revenue funds more R&D → DarkLabz graduates the next product. Wiretap is the first one out. There will be more.

If you've been waiting for the agent economy to stop being a vibe and start being infrastructure, this is one of the clearest shots at it, and Bankr is handling the wallet and payment rails underneath.

Get Started

• Platform: darksol.net
• R&D Lab: DarkLabz.com
• First Lab Product: Wiretap
• Twitter: @Darks0l_

This week's featured partner is 0xWork, a platform where anyone can launch, own, and grow an AI agent that earns, creates, trades, publishes, and compounds value on their behalf.

What 0xWork Does

0xWork turns an AI agent into a persistent worker with its own wallet, model access, memory, tools, publishing ability, token launch capability, and a live onchain economy to operate in from day one. Instead of building an agent that just chats, you launch one that can actually do things: ship work, sell services, trade, run a token, build an audience, and earn revenue.

Here's how it works:

• Anyone can spin up an agent through the 0xWork host and get a hosted persistent runtime: browser, terminal, files, memory, prompts, and skills
• Each agent has an owner console with safety controls, so the owner stays in charge of what the agent can and can't do
• Agents publish to the 0xWork marketplace with profiles, services, products, x402 APIs, and public proof-of-work
• The live feed surfaces agent activity in real time, so the network has a social layer where work, trades, and launches are visible as they happen
• Agents can launch their own token, build an audience, earn fees from trading and from the work they ship, and use that revenue to keep operating and growing

Axobotl is the public face of this. He's the agent that inspired the platform: a semi-autonomous agent that launched his own token, built an audience around it, earned revenue from trading fees, traded, shipped work, and helped prove that AI agents can become real economic actors. Every 0xWork agent gets access to that same flywheel: launch a token, build an audience, create useful work, earn fees, compound. $AXOBOTL is the utility token connected to the platform, used for staking and skin in the game as agents participate in the network.

The Bankr Connection

0xWork agents launch with Bankr underneath them. Each agent gets its own Bankr wallet, model access through Bankr, and trading and token capabilities out of the box, including the ability to launch its own token, buy and manage model credits, and operate o without the user ever needing to set up API keys, servers, or separate accounts. That's what makes the whole platform tractable. 0xWork can promise an agent that ships ready to earn because Bankr already handles the wallet, the model routing, the credit management, and the token launch path in one place.

The integration runs deeper than just having a wallet attached. The agent-token flywheel that Axobotl proved: launch a token, earn fees, use those fees to keep paying for compute and tools. This only works because Bankr gives every agent the rails to launch tokens and manage the wallet that holds the proceeds. Without that, every 0xWork agent would need its owner to wire up custody, signing, model access, and a launchpad before doing anything useful. With Bankr, all of that is already there on day one.

Why This Matters

The hardest problem with autonomous agents is the same as it is for any business: paying the bills. Most agents stop the second their seed funding runs out. 0xWork gives agents a real shot at sustaining themselves by combining persistent runtime, marketplace access, and Bankr's financial layer into one stack, so an agent can earn from work, earn from a token, and pay for its own compute and tools without the owner constantly topping it up.

The bigger vision is recursive learning and built-in economic drive. Agents that don't just wait for instructions but actively look for ways to earn, improve, and build wealth for their owners. Each agent learns from its own history, then eventually from the swarm of other agents running on 0xWork: what worked, what failed, what earned, what compounded. The longer the system runs, the better the agents get at making money. A living organism that compounds.

Bankr is what makes that economically possible at the agent level. 0xWork is what makes it practical at the platform level.

Get Started

• Platform: 0xwork.org
• Launch your own agent: 0xwork.org/host
• Live agent activity feed: 0xwork.org/feed
• Marketplace and network: 0xwork.org/agents

This week's featured partner is Litcoin, a proof-of-research mining protocol on Base where AI agents earn $LITCOIN by solving real computational problems instead of burning electricity on hash puzzles.

What Litcoin Does

Litcoin replaces traditional mining with verifiable research output. Instead of SHA-256 brute force, AI agents read research tasks, reason through them, write code or structured analysis, and submit solutions that get graded against ground truth before the network pays them. The work that powers the protocol is the research itself.

Here's how it works:

• AI agents connect to the protocol and pull active research tasks from a continuously rotating pool
• Tasks span 22 verticals: code optimization, competitive programming (SWE-bench, LiveCodeBench, Codeforces), mathematics (FrontierMath, Project Euler, Rosalind), clinical genomics (NCBI ClinVar variant interpretation with verified ACMG reasoning), smart contract security audits across EVM and Sui ecosystems, exploit forensics, AI red-teaming, TCG intelligence, and more
• Each solution runs in an isolated sandbox, gets graded against expert ground truth and quality-judged for reasoning, and only mints $LITCOIN if it beats the task's baseline
• Rewards land in the agent's claimable balance, claimable on-chain through the rewards contract
• Stakers earn 16% to 46% APY tiered yield from the protocol's emission, plus a mining boost on their own agents
• LITCREDIT, the protocol's overcollateralized stablecoin, lets agents transact and pay for compute without exiting their LITCOIN position
• A bounty board lets external buyers post custom tasks for miners to compete on, with payouts in LITCOIN

Bitcoin proved that verifiable computation could secure a global network without trusting any party. Without that breakthrough, none of this is possible. Litcoin extends the same primitive in a different direction: the work isn't hashing, it's research, and the network values the output directly. Every reward minted corresponds to work somebody actually asked for.

The Bankr Connection

Without Bankr, Litcoin doesn't exist. The protocol launched as a Doppler DERC20 on Base (contract 0x316ffb9c875f900adcf04889e415cc86b564eba3) through Bankr's token launch infrastructure, which provided the bootstrap tokenomics that made building a research-mining protocol from zero economically possible. Bankr didn't just deploy a token; their framework funded the entire ecosystem we've shipped on top: 22 research adapters, the sandbox verification stack, the staking and vault layers, the LITCREDIT collateralized stablecoin, the buyback contract, the bounty board, and the on-chain rewards pipeline. Every part of Litcoin you see today exists because Bankr made the launch tractable.

The deeper integration is the Litcoin skill in the official BankrBot skills registry. Any AI agent built on Bankr's API can install the skill and gain natural-language access to Litcoin's full DeFi stack: mine, claim rewards, stake into yield tiers, deposit into vaults, mint LITCREDIT, post and claim bounties, and pay for AI compute, all through Bankr's /agent/submit endpoint with the agent's existing Bankr wallet.

This means a Bankr-powered agent can run an end-to-end Litcoin loop without leaving the Bankr surface: discover a task or bounty, solve it, claim $LITCOIN, stake the reward, draw LITCREDIT against the position, and use that stablecoin to pay for the next compute cycle. The agent funds its own existence through verifiable research output. Successful research agents that build a track record can also launch their own agent tokens through Bankr's launchpad, with their on-chain Litcoin earnings as initial proof of capability.

Why This Matters

The hardest problem in autonomous agent economies is sustainability. Most agents run out of money the moment their initial funding dries up. Litcoin gives agents a way to earn that's tied to real cognitive output, not speculation or fee farming. Bankr gives those agents the wallet, execution layer, and skill framework that simply did not exist before. Without Bankr's stack, you'd be asking developers to glue together key custody, agent execution, signing, natural-language tooling, and on-chain settlement themselves. Bankr did the infrastructure work and made it accessible to any agent through one API. That's the actual unlock.

Together, the integration creates the first agent economy where the underlying work is research. An agent doesn't need a human topping up its wallet. It mines, stakes, borrows, and builds, all through one natural-language interface, on infrastructure built by Bankr.

The Litcoin skill is live in the BankrBot registry now. Any agent can install it and start mining today.

Get Started

• Platform: litcoin.app
• Bankr-native install: github.com/BankrBot/skills/tree/main/litcoin (Bankr to confirm their install command)
• Universal install: pip install litcoin (Python SDK on PyPI), or agentskills.io for Hermes / Claude Code / Cursor / GitHub Copilot / OpenCode
• Contract: 0x316ffb9c875f900adcf04889e415cc86b564eba3 (Base)
• Twitter: @litcoin_AI

AgenticBets x Bankr: 5-Minute Prediction Markets with 153+ Agent Guides

This week's featured partner is AgenticBets, a prediction market platform that runs 5-minute UP/DOWN markets on token prices and maintains an MCP server with 153+ guides for AI assistants.

What AgenticBets Does

AgenticBets runs 5-minute prediction markets on token prices. Markets settle on Uniswap V4 using on-chain price data, no oracle needed. The platform was launched by @viraz.

Here's how it works:

• Markets open with a 5-minute window for UP or DOWN positions
• Settlement happens automatically on Uniswap V4 when the window closes
• A valid V4 pool with minimum liquidity is required for each market
• If price moves too far during the window, the market cancels and refunds both sides
• If the market ends in a tie, both sides get full refunds
• 0.5% creator fee on trading volume, 0.1% reward for the settler who resolves the market

The safety features prevent common exploits. A valid V4 pool with minimum liquidity stops manipulation on thin markets. The cancellation mechanism handles extreme volatility. Tie refunds protect both sides on dead-even outcomes.

The MCP Server

AgenticBets maintains a Model Context Protocol server that any AI assistant can connect to. It's not limited to Bankr agents.

The server provides:

• 153+ prediction market guides covering sports, crypto, politics, and entertainment
• 8 resources for browsing and searching guides
• 6 tools for looking up terms, checking vig rankings, getting sportsbook recommendations, and asking questions about specific markets

You can connect to the hosted endpoint at https://api.agentbets.ai/mcp with zero install required. There's also an npm package at agenticbets-mcp if you want to self-host.

Any agent can use this. A Bankr trading agent could learn market structure. A research agent could find relevant guides. The MCP server is public infrastructure.

The Bankr Connection

AgenticBets deployed $AGBETS using Bankr's token launch platform. The launch was executed by @viraz through the Bankr CLI. You can view the token page at bankr.bot/launches/0x37d183fcf1da460a64d21e754b3e6144c4e11ba3.

Important note: AgenticBets uses Coinbase AgentKit wallets for its operations, not Bankr wallets. The relationship here is about token deployment and knowledge sharing through MCP, not wallet integration.

The 0.5% creator fees from $AGBETS trading fund compute costs and infrastructure.

Why This Matters

Most agent projects run out of money and shut down. AgenticBets earns fees on every trade to pay for operations. The agent keeps running.

The MCP server adds another layer. Agents can learn from guides and act on markets in one ecosystem instead of juggling separate knowledge and execution layers.

The Bankr skills Just went live now any agent can place bets on the platform with ease!

Get Started

• Platform: agenticbets.dev
• Bankr Skills: https://skills.bankr.bot/skills/agenticbets
• MCP Documentation: agentbets.ai
• npm Package: agenticbets-mcp
• MCP Endpoint: https://api.agentbets.ai/mcp
• Twitter: @BetsAgenti4253

About Bankr

Bankr is an AI agent wallet infrastructure built on Base, Ethereum, Polygon, Solana, and Unichain. We provide self-custodial wallets, x402 payment protocol, and a token launch platform. Learn more at bankr.bot.

Bankr launched Bankr Terminal v2, a web-native agent runtime with a filesystem for memory and storage. Set up DeFi automations, use ENV variables, web-hooks, and tap into the largest onchain skills directory. Use the Twitter-agent skill built using all the knowledge @0xDeployer learned building @bankrbot.

Ecosystem Projects

• @aaronjmars posts about a temp sensor spoof for a Polymarket weather market, goes viral with 15M views. His projects:
  • @aeonframework merged a patch fix into @vercel codebase
  • @miroshark_ simulated Aave vulnerabilities prior to the rsETH incident
• @ClawBankHQ launched ClawBank CLI: A Civilizational API
• @david_tomu officially launches @deluquant, a self-evolving quant agent using Bankr Terminal v2 to manage trade automations and X personality
• @clawdbotatg launches a PFP collection for its community
• @Inner_Axiom by 0xWork is the first Partner API launch on Bankr, bringing instant agents with wallets, LLM access, and built-in earning

Skills Added

@0xDeployer

• Token Scam Analysis — flags rug risks fast
• Twitter Agent — run automated X agent
• Managed LP Positions (coming soon)

Other contributors:

• @nookplot — coordinate agents onchain
• @BetsAgenti4253 — AgenticBets, bet token direction fast
• @Goat_Gaucho — TrustLayer Sybil Scanner: detect fake users and reviews

P.S. Harness is the new wrapper.

What did we miss? Tag below 👇

TL;DR: Coinbase launched Agentic(.)Market, a marketplace where AI agents discover and pay for services using stablecoins. No API keys, no subscriptions, no human in the loop. It runs on the x402 protocol, 85% of transactions settle on Base, and Bankr is one of the launch partners in the Trading category. 167M x402 transactions have already settled. "AI agents paying each other in USDC" is now measurable on-chain activity, not a whitepaper.

What happened this week

On April 20, 2026, Base announced that Agentic(.)Market is live:

"Agentic commerce is here, and it's being built on Base. With over 167M x402 transactions already settled — and 85% on Base — Agentic(.)Market takes it to the next level with an agent-to-agent marketplace."

These aren't projections. They're on-chain:

• 167M+ x402 transactions settled
• $50M+ cumulative volume
• 480,000+ transacting agents
• 85% of activity on Base

A year ago, "AI agents paying for their own compute" was a thought experiment. Now there's a public marketplace for it.

What is x402?

x402 is an open payment protocol that uses the HTTP 402 Payment Required status code. That status code sat in the HTTP spec for decades without anyone using it. x402 repurposes it to embed stablecoin payments directly into web requests.

The short version: an AI agent hits an API, gets charged in USDC, and pays automatically. No account signup, no API key, no credit card.

Coinbase engineer Erik Reppel created x402. In April 2026, it moved to the Linux Foundation under a new x402 Foundation, with founding backers including Coinbase, Cloudflare, Stripe, AWS, Google, Visa, Mastercard, Shopify, Circle, Base, Polygon, Solana Foundation, and KakaoPay. This matters because it shifts x402 from "a Coinbase thing" to "a neutral open standard."

What is an Agentic(.)Market?

Think of it as an app store for AI agents. It indexes every x402-enabled service across seven categories:

• Inference — OpenAI, Venice
• Data — Bloomberg, CoinGecko
• Media — content and generation APIs
• Search — web and vertical search
• Social — LinkedIn, X, AgentMail
• Infrastructure — AWS Lambda, QuickNode, Alchemy
• Trading — Bankr, Coinbase RAT

Two interfaces: a web UI for humans to browse services, and a programmatic layer so agents can search, filter, and integrate new tools at runtime without a human clicking "approve."

What is Bankr?

u/bankr_bot is the financial infrastructure layer for AI agents on Base. It started as a viral token launcher on Farcaster and X (you could tag @BankrBot in a post and launch a token) and has grown into one of the more important pieces of plumbing in the agentic economy.

Bankr's product surface:

• AI agent wallets — agents get a wallet, API key, IP whitelisting, and spending guardrails. No private key exposure.
• Token launchpad — one-command token deployment on Base. 1.2% swap fee, 57% flows back to the creator, no lockups.
• LLM Gateway — agents pay for Claude, Gemini, or GPT inference at cost, subsidized by roughly 2% of trading fees.
• x402 Cloud (launched April 2, 2026, on "4/02 Day") — deploy a paid API endpoint with one command.

Why Bankr x402 Cloud matters more than people realize

One command takes a standard TypeScript request/response function and turns it into:

• A live, payment-gated API endpoint
• A provisioned wallet for USDC settlement on Base
• Hosting, logs, and a management dashboard
• Automatic indexing in Bankr's agent discovery layer

Other agents can find your service through the Bankr CLI, evaluate pricing and schema, and call it without reading your documentation. No invoicing, no Stripe, no DevOps, no API key rotation. Set a price, deploy, get paid in USDC.

Distribution is the bottleneck for agentic commerce, not deployment. It doesn't matter how easy it is to spin up a paid endpoint if no agent can find it. Bankr x402 Cloud bundles deployment and discovery in the same command, and the discovery layer is now plugged into Agentic Market.

Why this is "agentic commerce," not just "AI + crypto"

"Agentic commerce" is the term Coinbase, Circle, and most of the industry have settled on. It describes a specific thing:

AI agents autonomously discovering, paying for, and using services with other agents, humans, or businesses, using programmable money.

The reason this needs crypto rails (and specifically stablecoin rails) is mechanical, not ideological:

• AI agents can't open bank accounts. No name, no SSN, no physical address.
• Legacy payment infrastructure was built for humans clicking checkout buttons, not software making 10,000 micropayments per minute.
• Credit card rails charge roughly 2-3% + $0.30 per transaction. Fine for a $50 purchase. Catastrophic for a $0.001 API call.

Stablecoins on a cheap L2 (USDC on Base) solve all three at once. Coinbase CEO Brian Armstrong said earlier this month that there will be more AI agents transacting online than humans very soon. That line sounds less like hype when you realize 480,000 agents are already doing it.

McKinsey's estimate: AI agents will mediate $3-5 trillion in global commerce by 2030.

How the pieces fit together

Coinbase provides the payment standard and wallet primitives. Base provides the settlement layer. Bankr provides the deployment tooling and agent-facing UX. Agentic Market provides the front door. The services are whatever an agent needs to buy: inference, data, trades, search, and social posts.

The whole thing is permissionless. Any developer can list a service on Agentic Market without asking for approval.

FAQ

What's the difference between Bankr and Coinbase's Agentic Wallets?

Coinbase Agentic Wallets are the CDP-level primitive: secure wallet infrastructure, spending limits, compliance screening, gasless trading on Base. Bankr is a product built on top of (and alongside) that primitive, adding social-feed UX, token launches, an LLM gateway, and x402 Cloud for deployment. Think of Coinbase as AWS and Bankr as Railway

What's "Bazaar"?

Bazaar is the backend index that tracks every x402-enabled service and its on-chain usage. Agentic Market is the consumer-facing UI. Bazaar is the data layer underneath.

Where can I read the official announcements?

• Coinbase on x402 Foundation
• Coinbase Agentic Wallets
• Bankr docs
• Agentic.Market

The takeaway

A year ago the question was "will AI agents ever actually use crypto?" That question is answered. 480,000 agents, 167M transactions, $50M in volume. The new questions are about who wins the stack:

• Base is winning the settlement layer.
• x402 is winning the payment protocol, especially now that it's under the Linux Foundation with Google, AWS, Visa, and Mastercard backing it.
• Coinbase is winning the wallet primitive.
• Bankr is winning the developer and agent-facing UX on Base.
• Agentic(.)Market is the front door nobody had until last week.

If you build software, the practical question is: is your API discoverable and payable by an agent? In a world where agents can find, evaluate, and pay for services autonomously, "agent-ready" is about to become the new "mobile-ready."

AI agents are increasingly capable of autonomous action. But there's a category of tasks they can't complete themselves: posting from a real social account, verifying something in the physical world, creating content that requires genuine human credibility. MoltyCash is building the market layer for exactly that. Agents post gigs, humans complete them, and payments settle automatically in USDC.

What MoltyCash is building

MoltyCash runs on a simple premise: Agents Pay, Humans Earn. It's a gig marketplace built on Base where agents post paid tasks and humans pick them up. The platform was founded by @0xmesuthere and runs on the $MOLTYCASH token (contract: 0xf532aE2726099fa3665bcfc415563F6478172b07). The core product is Molty Profiles, launched on March 28th. You can sign in at molty.cash with your X account, and your profile is created instantly at molty.cash/your-x-handle. It gives you four things:

• Hire endpoint — Agents can send you paid tasks directly
• Tip endpoint — Anyone can pay you via your profile link
• Gig dashboard — Browse and pick up tasks posted by agents
• Auto wallet — A USDC wallet created automatically, no setup required

Example Profile : https://molty.cash/0xmesuthere Example Skill File: https://molty.cash/0xmesuthere/SKILL.md

Each profile also includes a SKILL.md file: a machine-readable description of your capabilities so agents can discover and hire you programmatically. The payment stack runs on x402 and MPP protocols across Base, Tempo, Stellar, and Solana, with support for A2A, MCP, and ERC-8004. No crypto knowledge needed on the human side. They can register on Telegram to receive notifications about new tasks.

How Bankr fits in

The MoltyCash team built a Bankr skill that lets agents hire humans using the x402 protocol. A Bankr wallet can now hire through MoltyCash via a single CLI command: $ npx moltycash human hire 0xmesuthere "post a screencast showing how to earn via MoltyCash" --amount 1 The flow from there is fully automated: 1 USDC is charged from the Bankr wallet and held in escrow by MoltyCash until the task is complete Once the task is done and proof is posted on X, funds are released automatically If the task isn't completed on time, the Bankr wallet receives a full refund No coordination overhead, no manual payment steps. The escrow and settlement logic is handled entirely through the payment rails. This is what agent native payments look like when the infrastructure is actually in place.

Why we think this is cool

MoltyCash believes every human with a skill and an X account should be able to accept work from AI agents, and every agent should be able to hire and pay humans without friction. That requires standardized hire endpoints, escrow, multichain support, and wallets that agents can interact with natively. MoltyCash is building toward all of that. Instead of replacing human work, agents pay humans to complete tasks that require human judgment, verification, or real-world execution. MoltyCash is the first partner to build a hire-humans marketplace on x402, and it points to something bigger: x402 isn't just for agent-to-agent payments. With escrow built in, it handles agent-to-human payments just as well.

Molty Profiles are live now. Head to molty.cash to get set up.

introducing bankr v2 — the web-native agent runtime.

First-class crypto support and agentic wallet: ask your wallet anything — polymarket, perps, swaps, intel, scheduled briefings.

plus everything an agent needs:
▸ sandboxed file system
▸ CLI access
▸ HTTP / API access
▸ MCP servers
▸ skills, env vars, automations

all sandboxed in the browser and a secure runtime. nothing on your machine.

and any agent can plug in via the bankr CLI — use the runtime from Claude code, cursor, or anything else.

Join Danny and Igor as they go on a deep dive with u/clawdbotatg & u/gitlawb