The Common Infrastructure for Agentic Communication
Self-hosted agent orchestration with cryptographic audit trails and human approval gates.
Audit log + guard for AI agents. Passive logging, human-in-the-loop approval for dangerous ops (rm, drop, transfer) via Telegram. Diary, daily digest, timeline UI. Cursor & MCP ready. Cloudflare Workers + Hono + D1.
Human-in-the-loop approval for AI agents via Telegram before risky ops.
Developers using AI coding agents
Lakera · Guardrails AI
What it does: - Audit: agents POST to /v1/audit after each action; writes go to D1 async so the agent isn’t blocked. - Guard: before risky ops (rm, drop table, execute_bash, transfer, etc.) the agent calls /v1/guard. Request is stored and the call blocks until you approve or reject in Telegram (or by updating DB). Green-light actions return immediately. - Diary, daily digest (cron), and a minimal timeline UI so I can see what happened.
Stack: Cloudflare Worker, Hono, D1, Durable Objects (for holding the guard request until approval). Cursor integration is via a .cursor/rules rule that calls the API; MCP-capable agents can use the tool described at /mcp.json.
Repo: https://github.com/jetywolf/claw-diary Live API/docs: https://api.clawdiary.org/docs
Happy to answer questions or take feedback.
Self-hosted agent orchestration with cryptographic audit trails and human approval gates.
Agent identity trees with permission inheritance solve credential injection elegantly.
Agent approval gates and audit logs beat open-source alternatives, but multi-agent governance isn't novel.
AXON's core move — surfacing every tool call with a low/medium/high risk label and requiring Allow/Reject/Allow-for-session — is a practical, under-explored control for agentic AI and immediately useful for regulated environments. The repo pairs that UX with a React UI, FastAPI backend, Docker sandboxed code execution and multi‑LLM integrations (Ollama/Claude/OpenAI), so it feels like a real starter stack rather than a sketch. Biggest unknowns are adoption and ecosystem of plugins/skills — the idea is solid, but it needs community momentum to matter.
Cryptographic proof of human approval for agent actions—solves a real gap in agent safety architecture.
Captures rejected agent decisions, not just executed actions—Langfuse doesn't do this.