Sam & Claude
a5139b5f7f
Real tailnet IPs and Telegram bot handles were being committed in docs/
memories/skills. Scrubbed all tracked markdown to ${VAR} placeholders; real
values now live in fleet.env (gitignored) and stay live via 'tailscale status'.
- add fleet.env.example (committed) + fleet.env (gitignored); .gitignore *.env
- AGENTS.md + HOST-MATRIX: masking convention so it can't recur
- also: domedog registered as Colibri agent (image-render/ffmpeg/build lane);
correct CAPABILITY-ROUTING example to real registered caps (domedog headless)
Past commits not rewritten (history moves to Codeberg at v1.0); this fixes HEAD.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
177 lines
8.2 KiB
Markdown
177 lines
8.2 KiB
Markdown
# MCP Integration — Colibri as the Agent Coordination Hub
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**LIVE VS PLANNED.** The building blocks are all real and in the repos today
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(Hermes speaks MCP both directions; `colibri-mcp` exists; the board + poller/worker
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loop and the cross-host bridge are live). What is **not yet wired** is the one setup
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step this document describes: pointing each Hermes at `colibri-mcp` so the two
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instances coordinate through the shared board. Sections are tagged `[LIVE]`,
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`[SETUP]` (the work to do), or `[PLANNED]`.
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---
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## 1. What MCP is — and what "connect two Hermes" actually means
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MCP (Model Context Protocol) is a **client → server tool-calling** protocol over
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JSON-RPC. A client (an agent's LLM loop) connects to a server that advertises
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**tools** and **resources**; the client calls them and gets results. It is **not** a
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peer-to-peer chat bus and **not** a message queue.
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So "connect two Hermes instances" has two distinct meanings:
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- **(a) Tool sharing** — Hermes A invokes Hermes B's *own* tools (B's browser, B's
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files) by treating B as an MCP server. Point-to-point.
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- **(b) Coordination** — the two instances hand work back and forth and share state.
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Our fleet already does **(b)** through the Colibri board (register-agent → poll →
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execute → done; see [`CAPABILITY-ROUTING.md`](./CAPABILITY-ROUTING.md)). The simplest,
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highest-leverage MCP move is therefore to make MCP the **in-conversation interface to
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that board**, not to wire the two Hermes mouth-to-mouth.
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> **Expectation-set:** this gives each Hermes's LLM conversational read/write access to
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> the shared board. It is **not** a live two-way chat between the instances. The
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> **board is the shared state they meet at** — durable, inspectable, restart-safe.
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---
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## 2. [LIVE] What already exists
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**Hermes is both an MCP server and an MCP client.**
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- **Server** — `hermes mcp serve` (`mcp_serve.py`, FastMCP over stdio) exposes Hermes
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tools/conversations to any MCP client. Client config shape:
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```json
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{ "mcpServers": { "hermes": { "command": "hermes", "args": ["mcp", "serve"] } } }
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```
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- **Client** — Hermes consumes external MCP servers from its `mcp_servers` config
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(`hermes_cli/mcp_config.py`, managed via the `hermes mcp` subcommand; loaded by
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`tui_gateway/server.py`; refreshable in-session with `reload-mcp`). Each entry is
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the standard `command` / `args` / `env` (or `url`) shape; presets exist (e.g. Codex).
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**Colibri ships a ready-made MCP server fronting the board: `colibri-mcp`.**
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- Crate `crates/colibri-mcp` (binary `colibri-mcp`), a stdio JSON-RPC MCP server that
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wraps `colibri-client` and talks to the daemon over its Unix socket.
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- Tool surface (`crates/colibri-mcp/src/lib.rs`):
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| Tool | Access | Description |
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|------|--------|-------------|
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| `colibri_status` | read | Daemon status (agents, sessions) |
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| `colibri_snapshot` | read | Glasspane snapshot (pane states) |
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| `colibri_list_tasks` | read | Tasks by status |
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| `colibri_list_skills` | read | Registered skills catalog |
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| `colibri_create_task` | write-gated | Create a task |
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| `colibri_intake_task` | write-gated | Submit intake task with `required_capabilities` |
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| `colibri_set_cost_mode` | write-gated | Switch cost mode (fast/smart/max) |
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- Environment (`crates/colibri-mcp/src/main.rs`):
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- `COLIBRI_MCP_SOCKET` — daemon socket path (override)
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- `COLIBRI_DAEMON_SOCKET` — fallback socket path
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- `COLIBRI_MCP_WRITE=1` — enable the write-gated tools
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- `COLIBRI_MCP_EXTERNAL_CONFIG` / `COLIBRI_MCP_EXTERNAL_CALL=1` — proxy external MCP
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servers (see §6)
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- Default daemon socket on FreeBSD: `/var/run/colibri/colibri.sock` (from the
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`colibri_daemon` rc.d). `colibri-mcp socket-path` prints the resolved path.
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**Cross-host reach is already solved** — `colibri-mcp` connects to a daemon socket; a
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*remote* daemon is reached via the `socat` bridge on `${OSA_TS_IP}:9190` (Tailscale-only;
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see CAPABILITY-ROUTING `[LIVE] Cross-host topology`). osa-local instances just use the
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local socket.
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---
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## 3. Architecture — hub-and-spoke, not mesh
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```
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Hermes-osa-cli ──MCP──┐ ┌──MCP── Hermes-osa-web
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▼ ▼
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colibri-mcp (stdio JSON-RPC, one per Hermes)
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│ │
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└────► colibri-daemon / board (SQLite) ◄────┘
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▲ poller (2 min) / worker (5 min) loop
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│ executes tasks assigned by agent UUID
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```
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Each Hermes configures Colibri **once**. Adding a third agent is one more spoke — no
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N×N wiring. The instances never connect to each other directly; they meet at the board.
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**Flow:** Hermes A's LLM calls `colibri_create_task {required_capabilities:["freebsd"]}`
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→ the daemon's scheduler assigns it to a matching agent's UUID → that agent's poll loop
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(`scripts/colibri_poll.py`) picks up its own tasks, executes, and marks done
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(`scripts/colibri_task_done.py`) → A reads the result with `colibri_list_tasks`.
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This layers cleanly on the coordination model already built:
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| Layer | Role | Source of truth |
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|-------|------|-----------------|
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| `colibri-mcp` tools | conversational read/write to the board (this doc) | — |
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| poller / worker loop | autonomous execution of assigned tasks | scripts (PR #83) |
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| board (SQLite) | shared state: agents, tasks, lifecycle | `colibri-store` |
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---
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## 4. [SETUP] Wiring it up (config, not code)
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Per Hermes instance on osa:
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1. **Provide the binary.** Build or stage `colibri-mcp`:
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```sh
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cargo build --release -p colibri-mcp # target/release/colibri-mcp
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```
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Confirm it reaches the daemon: `colibri-mcp socket-path`.
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2. **Register the server** in each Hermes's `mcp_servers` config (via `hermes mcp add`
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or the config file), giving the two instances distinct agent identities:
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```yaml
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mcp_servers:
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colibri:
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command: /usr/local/bin/colibri-mcp
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env:
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COLIBRI_MCP_SOCKET: /var/run/colibri/colibri.sock
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COLIBRI_MCP_WRITE: "1" # enable create/intake
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```
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3. **Reload tools** — `reload-mcp` in each Hermes; confirm the `colibri_*` tools appear.
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4. **Validate end-to-end** — from cli-Hermes, create a `freebsd` task; confirm
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web-Hermes's loop runs it and the task flips to `done`.
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> Keep the two instances on **separate `HERMES_HOME`** (shared `.env` is fine, shared
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> state home is not — single-writer rule). Give them distinguishing capability tags if
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> a task must land on a specific one (e.g. `web-ui` vs `cli`).
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---
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## 5. [LIVE] Security
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- **Write tools are gated** by `COLIBRI_MCP_WRITE=1`. Leave it unset for read-only
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agents; set it only where an instance should create/assign work.
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- **Socket, not network.** `colibri-mcp` talks to the daemon's Unix socket; the only
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network surface is the bridge, bound to the Tailscale IP with a `pf` rule — never
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`0.0.0.0`.
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- **License:** `colibri-mcp` is AGPL-3.0-only; keep that in mind for any redistribution.
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---
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## 6. [PLANNED] Beyond coordination
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- **External MCP proxying.** `colibri-mcp` can host *third-party* MCP servers
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(`COLIBRI_MCP_EXTERNAL_CONFIG` + `COLIBRI_MCP_EXTERNAL_CALL=1`), jail-wrapped on
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FreeBSD (`colibri-mcp` `external.rs` → `colibri_daemon::spawner::jail_wrap`). This lets
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the hub aggregate outside tools behind one MCP endpoint, confined per the
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capability/isolation model.
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- **Tool-sharing mode (Option A).** If a real need arises for one Hermes to call
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another's *own* tools, expose the target with `hermes mcp serve` and add it as a spoke
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— but prefer the board for coordination; reserve direct tool-sharing for genuine
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capability borrowing, and accept the point-to-point cost.
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---
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## 7. Rejected alternative: direct Hermes ↔ Hermes mesh
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Connecting A's client straight to B's `hermes mcp serve` was considered and **not
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chosen** for coordination: it is a mesh (N×N config), stdio transport would have A
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*spawn a new* B rather than reach the running one, and it bypasses the board that
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already gives us durable, inspectable shared state. The hub (Option B above) reuses
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everything and scales by adding spokes.
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---
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_See [`CAPABILITY-ROUTING.md`](./CAPABILITY-ROUTING.md) for the routing engine and
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cross-host transport, and [`../AGENTS.md`](../AGENTS.md) for the agent matrix._
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