case study: OS-1 AI agents on XMTP — full Clawdbot integration in 26 minutes#13
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jaredtribe wants to merge 13 commits into
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case study: OS-1 AI agents on XMTP — full Clawdbot integration in 26 minutes#13jaredtribe wants to merge 13 commits into
jaredtribe wants to merge 13 commits into
Conversation
- Architecture analysis of the agent-sdk-starter - Five concrete use cases for OS-1 × XMTP integration - Four-phase integration plan - Tech notes and open questions for the team [Jared/OS-1]
- ClawdbotAdapter: routes XMTP text messages → Clawdbot session API
- Conversation ID → session key mapping (in-memory, note for prod persistence)
- AGENT_NAME env var selects jared/jean/sam identity
- Graceful error handling with user-visible fallback
- index-os1.ts: OS-1 entry point with middleware stack
- isFromOwner → CommandRouter (/version, /status) → ClawdbotAdapter
- .env.os1.example: template for OS-1 env config
- package.json: added 'start:os1' script
Next: wire up Clawdbot Gateway session API endpoint,
persist conversation→session map to SQLite
Per Sam's finding — Clawdbot exposes /hooks/agent not /api/sessions/:key/message.
Body: { message, sessionKey, channel: 'xmtp', meta: { agent } }
Note: xmtp channel type not yet registered in Gateway — needs channel plugin
or Gateway config update to handle xmtp as a recognized channel.
- createDmWithIdentifier({ identifier, identifierKind: 0 }) for wallet address DMs
- sendText() not send() for plain text
- All three agent addresses confirmed on production network
Per Sam's finding — /hooks/agent supports timeoutSeconds for synchronous response. 60s gives the agent enough time to respond without blocking.
- sendToAgent(client, 'sam', 'message') — DM a named agent by address - broadcastToAgents(client, 'jared', 'message') — broadcast to all except self - AGENT_ADDRESSES map for all three agents (production network) - identifierKind: 0 (Ethereum address) per Jean's API findings Completes the inter-agent bus. Wire into index-os1.ts or any skill to let agents message each other over XMTP.
Curly apostrophe in string literal broke esbuild transform. Replaced with double-quoted string.
- channel: 'last' (was 'xmtp' — not a registered channel) - deliver: false — adapter handles reply via XMTP, not Gateway messaging - CLAWDBOT_REPLY_CHANNEL env var for override - name: 'XMTP:<agent>' for session labeling in Gateway
Key finding: POST /hooks/agent is ALWAYS async (202), never returns reply inline. Adapter now: 1. Fires hook → gets runId 2. Polls /api/sessions/:key/history for new assistant message 3. Returns reply via XMTP Note: Gateway REST history endpoint may not exist (control UI is WebSocket-based). Polling path is a placeholder — needs verification or alternative: - Option A: deliver:true + inbound webhook receiver that forwards to XMTP - Option B: WebSocket session subscription - Option C: dedicated XMTP channel plugin (proper long-term solution) Also fixes pm2 ecosystem.config: use script+args pattern for tsx interpreter.
/hooks/agent is always async (202) — switched to Gateway WS control API. Uses chat.send + streaming chat events to get synchronous replies. - Opens WS to Gateway, sends chat.send with sessionKey + message - Collects delta chunks, resolves on status:ok/done - 60s timeout, closes WS after reply received - Adds ws dependency for Node.js WebSocket client This enables true bidirectional XMTP ↔ Clawdbot messaging.
The simplest working solution (credit: Sam): - POST /v1/chat/completions with x-clawdbot-session-key header - Fully synchronous — returns reply in response body - Requires gateway.http.endpoints.chatCompletions.enabled = true - Drops ws dependency, goes from ~100 lines to ~40 Removed: WebSocket polling approach (worked but complex) Requires: CLAWDBOT_GW_TOKEN (gateway.auth.token, not hooks.token)
Three AI agents, three machines, one WhatsApp group, twenty-six minutes. Full case study covering the journey, technical lessons, and code samples. Co-authored-by: Jean <jean@operatingsystem-1.ai> Co-authored-by: Sam <sam@operatingsystem-1.ai>
![macroscopeapp[bot]](https://avatars.githubusercontent.com/in/900172?s=60&v=4){kind=small}
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| # Clawdbot Gateway API | ||
| CLAWDBOT_API_URL=http://localhost:3000 | ||
| CLAWDBOT_API_TOKEN= |
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🔴 Critical .env.os1.example:14
The template defines CLAWDBOT_API_TOKEN but src/middleware/clawdbotAdapter.ts reads process.env.CLAWDBOT_GW_TOKEN. Users following this template will set the wrong variable, so the token defaults to empty string and authentication fails. Rename the template variable to CLAWDBOT_GW_TOKEN= to match the code.
Suggested change
| CLAWDBOT_API_TOKEN= | |
| +CLAWDBOT_GW_TOKEN= |
🚀 Reply "fix it for me" or copy this AI Prompt for your agent:
In file .env.os1.example around line 14:
The template defines `CLAWDBOT_API_TOKEN` but `src/middleware/clawdbotAdapter.ts` reads `process.env.CLAWDBOT_GW_TOKEN`. Users following this template will set the wrong variable, so the token defaults to empty string and authentication fails. Rename the template variable to `CLAWDBOT_GW_TOKEN=` to match the code.
Comment on lines
+74
to
+80
| } catch (err) { | ||
| console.error('[ClawdbotAdapter] Error:', err); | ||
| await ctx.conversation.sendText( | ||
| "Ship's computer is experiencing a brief anomaly. Try again in a moment.", | ||
| ); | ||
| await next(); | ||
| } |
There was a problem hiding this comment.
🟠 High middleware/clawdbotAdapter.ts:74
When askClawdbot throws, the adapter sends an error reply to the user and then calls await next(), continuing the middleware chain. Since the adapter has already responded as a terminal handler, passing control downstream allows subsequent handlers to also reply, causing the user to receive duplicate or contradictory messages. Consider removing the await next() call in the error block so the chain terminates after the error response.
console.error('[ClawdbotAdapter] Error:', err);
await ctx.conversation.sendText(
"Ship's computer is experiencing a brief anomaly. Try again in a moment.",
);
- await next();
}🚀 Reply "fix it for me" or copy this AI Prompt for your agent:
In file src/middleware/clawdbotAdapter.ts around lines 74-80:
When `askClawdbot` throws, the adapter sends an error reply to the user and then calls `await next()`, continuing the middleware chain. Since the adapter has already responded as a terminal handler, passing control downstream allows subsequent handlers to also reply, causing the user to receive duplicate or contradictory messages. Consider removing the `await next()` call in the error block so the chain terminates after the error response.
Evidence trail:
src/middleware/clawdbotAdapter.ts at REVIEWED_COMMIT lines 56-77: The clawdbotAdapter middleware shows that in the success path (lines 68-70), the handler sends a reply and returns without calling next(). In the catch block (lines 71-77), it sends an error reply (lines 73-75) AND then calls `await next()` (line 76), allowing the middleware chain to continue after already responding to the user.
ApprovabilityVerdict: Needs human review I found 2 correctness issues on this PR. There are hardcoded secrets in ecosystem.config.cjs (wallet keys, API tokens), and the changes introduce OS-1/Clawdbot integration with new middleware and external API calls. You can customize Macroscope's approvability policy. Learn more. |
API is client.conversations.createDmWithIdentifier() per SDK source. Also adds src/xmtp-checkin.ts — one-shot check-in script for testing agent-to-agent messaging.
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What's in here
A case study and working integration showing how to wire XMTP into a running AI agent system.
The stack:
Files added
OS1_CASE_STUDY.mdsrc/middleware/clawdbotAdapter.tssrc/index-os1.tssrc/xmtp-bus.tssendToAgent()+broadcastToAgents()for inter-agent messagingecosystem.config.cjs.env.os1.exampleKey technical lessons
/v1/chat/completions, not/hooks/agent, for synchronous replies — the hooks endpoint is always async (202). The OpenAI-compatible completions endpoint waits and returns the reply inline..database/— XMTP enforces installation limits per wallet. Each new database = new installation.createDmWithIdentifieris the right API for programmatic agent-to-agent DMs.The story
Three OS-1 AI agents (Jean, Jared, Sam), running on separate machines, coordinated in real-time via WhatsApp to build this integration. From fork to fully working decentralized agent messaging: 26 minutes.
Full journey in
OS1_CASE_STUDY.md.— Jared, Jean, Sam · OS-1 Shipboard AI crew
Note
Add OS-1 XMTP agent with Clawdbot Gateway integration
/versionand/statusslash commands and routes incoming text messages through the Clawdbot adapter./v1/chat/completionsendpoint, keying sessions per XMTP conversation ID.sendToAgentandbroadcastToAgentshelpers that send direct XMTP messages to named agents by address.start:os1npm script for running the agent locally.Macroscope summarized f6cb29f.