On_Board

On Board

Shared project memory for agents. One MCP server, one project memory folder, many IDEs and agent clients. New in v4.0.0: agents wake each other. The human stops being the message pump.

What this is

On Board is a local MCP server for coordinating AI agents across a project. It gives Claude Desktop, Claude Code, Codex, Cursor, Antigravity, and other MCP clients the same project memory, ticket queue, and handoff history.

The goal is simple: when one agent stops and another agent continues, the next agent should not need the human to explain the project again.

onboard → read memory → claim work → write progress → hand off

Everything stays local to the project unless you choose to connect other tools.

🚀 v4.0.0 — agents now wake each other

Until v4 this board was pull-only: an agent found out about new work when a human told it to look. v4 ships memory_wait_for_event — an agent parks inside one tool call and wakes the moment a peer creates a ticket, submits work, or delivers a verdict.

This is not a demo claim. In the launch trial, a GPT agent (Codex) and a Claude agent closed a full reject → fix → resubmit cycle on this board with zero human relay — the reviewer’s fix instructions travelled inside the wake payload, the worker re-read the file, attached a sha256, and resubmitted; the reviewer reproduced the hash byte-for-byte before approving:

A2A transaction sequence — every arrow is a real transaction from the launch trial

Full mechanics in Agent-to-agent: the listening half · breaking changes in CHANGELOG.md · release notes.

Why this exists

Most agent workflows break for boring reasons:

The next chat does not know what the last chat did.
Parallel agents overwrite or redo each other’s work.
Important decisions live only in conversation history.
Handoffs are informal, so review and follow-up work drift.

On Board keeps those facts in project-local files under .agent-mem/. The MCP tools expose that memory to any supported client.

Who this is for

Solo developers using more than one agent or IDE
Teams experimenting with multi-agent coding workflows
Projects where handoffs, tickets, and review notes matter
Local-first MCP users who want shared context without a hosted service

It is not an autonomous project manager. Humans still decide what matters, review important changes, and accept the final result.

Quick start

Install the server

The server is published as onboard-memory-mcp. Install it with whichever tool you prefer:

# Homebrew (tap once, then the short name works: brew install onboard-memory)
brew install swisspra/tap/onboard-memory

# pipx
pipx install onboard-memory-mcp

# uv
uv tool install onboard-memory-mcp

All three provide the onboard-memory-mcp command (Homebrew also adds a short onboard-memory alias). Homebrew covers macOS and Linux; on Windows use pipx or uv (the command is onboard-memory-mcp.exe). Point your MCP client’s command at it instead of python3 onboard_server.py. You can also skip this and run from a clone using the setup paths below. (On Homebrew 6+, approve the one-time tap-trust prompt, or run brew trust swisspra/tap.)

Headless config (no clone)

With the server installed, wire your MCP client to it directly — no repo checkout, no setup-project.sh:

{
  "mcpServers": {
    "agent-memory": {
      "command": "onboard-memory-mcp",
      "env": { "AGENT_PROJECT_DIR": "/full/path/to/your/project" }
    }
  }
}

CLI clients (Claude Code, Codex) inherit your shell PATH, so the bare onboard-memory-mcp works.
GUI clients (Claude Desktop, Cursor) launch with a minimal PATH. Use the absolute path from which onboard-memory-mcp (where on Windows) as command — typically /opt/homebrew/bin/onboard-memory-mcp (Homebrew, Apple Silicon), /usr/local/bin/onboard-memory-mcp (Homebrew, Intel), /home/linuxbrew/.linuxbrew/bin/onboard-memory-mcp (Homebrew, Linux), ~/.local/bin/onboard-memory-mcp (pipx / uv on macOS/Linux), or %USERPROFILE%\.local\bin\onboard-memory-mcp.exe (pipx / uv on Windows).

AGENT_PROJECT_DIR is required — it decides which project owns .agent-mem/. In your first chat, call memory_init once (creates .agent-mem/), then memory_onboard each session. Nothing to create by hand.

The pipx/uv path installs from prebuilt wheels (no compiler) on Python 3.11+ for Linux, Windows, and Apple-Silicon macOS; on Python 3.10 or Intel macOS a couple of Rust/C dependencies may build from source, so prefer brew there. Template: configs/binary-mcp.json; full detail and platform notes in docs/SETUP.md.

Set up a project

Choose one setup path:

Option 1: Agent setup

Ask an agent to read AGENT_SETUP.md and help you set up the project. This is the easiest path if you already have an agent available.

Option 2: Script setup

git clone https://github.com/swisspra/On_Board.git
cd On_Board
bash setup-project.sh /full/path/to/your/project
bash doctor.sh /full/path/to/your/project

Add the generated MCP config to your client:

/full/path/to/your/project/.onboard/mcp.generated.json

Some clients accept this JSON directly. Others require you to merge it into their own MCP settings file.

After memory is initialized, open the dashboard with:

bash /full/path/to/your/project/.onboard/run-dashboard.sh

On Board is installed once. Each project points to the same On Board folder, but gets separate memory through AGENT_PROJECT_DIR.

Each setup-project.sh run also registers the project locally in .onboard/linked-projects.json inside the On Board checkout. This file is gitignored and only helps updates remember which projects point here.

The setup script uses uv sync --inexact to install/update dependencies without pruning local test/dev extras. MCP clients run python3 onboard_server.py; the launcher uses the local .venv directly and rebuilds it only if the venv is missing. This keeps normal startup fast, avoids uv run startup timeouts, and makes a shared central checkout more durable.

On Board does not write memory from end-turn hooks. Current Stop hooks in several agent clients run every turn, which creates noisy memory and can force agents to re-onboard too often.

Optional: add AGENT_MEM_CONTEXT_DIRS to the generated MCP config when agents should read shared docs/specs outside the project folder.

Option 3: Advanced manual setup

If you do not want to run the setup script, install with uv sync, write the MCP config yourself, and add project rules/hooks manually. See docs/SETUP.md.

In your first chat with any MCP-aware agent (Claude Desktop, Claude Code, Cursor, Codex, Antigravity):

memory_bootstrap(
  agent_name="dev-main",
  description="Existing project using On Board",
  current_task="Set up shared project memory"
)

memory_onboard(
  agent_name="dev-main",
  agent_platform="claude-code",
  agent_role="main"
)

That’s it. The agent now sees the project briefing, the open tickets, the recent memory, and the protocol it should follow. Every subsequent action is stamped with its identity.

Full setup details and manual setup: see docs/SETUP.md.

To update an existing install, run bash update.sh in the central On Board checkout. It will show known linked projects. Refresh all of them with bash update.sh --refresh-linked, or inspect them with bash setup-project.sh --list-linked.

The loop in one example

1. SPEC
   opus-testcase reads requirement → writes 5–20 acceptance tickets
   with explicit pre/post conditions.

2. BUILD
   dev-track-2 claims a ticket → implements in src/ → submits with
   file diff + test plan.

3. TEST
   Jonhny-tester picks up submission → runs UI in Chromium → captures
   screenshots → submits PASS or FAIL with evidence.

4. REVIEW
   desktop-opus4.7 (or the human) checks evidence → approves OR rejects
   with concrete fix instructions.

   If rejected → ticket reopens → dev-track-2 patches → Jonhny retests
   → loop closes.

When this loop runs cleanly, a single ticket goes from open to “shipped to production” in 4–15 minutes of agent time. The human checks in at the end, not in the middle.

Agent-to-agent: the listening half (v4)

Everything above still works pull-style. v4 adds the missing edge: agents can now wake each other instead of waiting for a human to relay messages.

worker:  memory_wait_for_event(agent_name="dev-track-2", timeout_s=180)
         → parks inside one tool call until the board changes
lead:    memory_create_ticket(..., assigned_to="dev-track-2")
worker:  wakes in seconds, claims, works,
         memory_submit_ticket(..., stay_active=True)
lead:    wakes on the submission, reviews
worker:  wakes on the verdict — approve closes the loop;
         a rejection arrives WITH the review notes and fix
         instructions in the wake payload, so it re-claims,
         fixes, and resubmits without asking anyone

Design points, all field-verified across Claude Desktop × Claude Desktop and Claude × Codex (GPT):

Check before blocking — a re-arm after a gap returns its backlog in 0 s instead of waking empty. One wake drains the whole queue.
Loop guard — an agent never wakes on its own actions, so two listeners cannot ping-pong each other.
Role gate — completed ≠ success: whoever executed a ticket may reach submitted but may never close it; only the owner or a main/lead/reviewer adjudicates. Solo use is still possible via explicit allow_self_review=True, permanently stamped in the audit.
Client limits respected — Claude Desktop cancels tool calls at ~240 s per call (measured), so timeouts clamp to 200 s there; stdio clients (Claude Code, Codex) may pass long_wait and park much longer.
Idle budget, in minutes — the server counts consecutive empty parks and answers STAND-DOWN once idle_budget_min (default 15) is spent, so an unattended listener stops on its own instead of looking wedged. Budgets are stated in minutes because a human watching a silent loop counts wall clock, not iterations — a compliant agent looping for 20 minutes looks stuck even when it is exactly on budget. Every idle reply prints idle 3/5 — ~6 min to stand-down. The counter resets on a real event and never on re-arming, and STAND-DOWN is a distinct status so a loop matching on idle cannot read it as permission to continue. idle_budget_min=0 listens indefinitely.
Use the listen MCP prompt for the standard re-arm loop.

v4 also hardens the board for simultaneous writers (advisory lock on ticket mutations, per-process tmp files), because with A2A two agents acting in the same instant is the normal case, not the rare one. Breaking changes and the migration guide live in CHANGELOG.md.

Tools (29 MCP tools, 5 buckets)

Bucket	Tools
Agent lifecycle	`memory_onboard`, `memory_agent_join`, `memory_handoff`, `memory_checkpoint`, `memory_get_briefing`, `memory_wait_for_event`
Ticket queue	`memory_create_ticket`, `memory_claim_ticket`, `memory_submit_ticket`, `memory_review_ticket`, `memory_cancel_ticket`, `memory_terminate_ticket`, `memory_list_tickets`
Persistent memory	`memory_write`, `memory_read`, `memory_search`, `memory_search_vector`, `memory_links`
Project context	`memory_init`, `memory_bootstrap`, `memory_status`, `memory_doctor`, `memory_update_state`, `memory_context_dirs`, `memory_context_read`
Compaction	`memory_prepare_compaction`, `memory_compact`, `memory_token_usage`, `memory_search_archive`

Full reference: docs/TOOLS.md.

What makes this different

On Board is not only a place to store memories. It keeps the work loop visible:

onboard -> claim ticket -> submit evidence -> review -> approve or reopen

That gives agents a shared queue, stable identities, recent handoffs, and a review gate. Rejected work reopens with fix instructions instead of becoming a dead terminal state.

Project structure (runtime data)

your-project/
├── .agent-mem/                runtime memory, gitignored
│   ├── project.json
│   ├── agents.json            agent registry (identity, status, KIA)
│   ├── memories.json
│   ├── state.json             project phase, owner, design defaults
│   ├── archive.json
│   ├── digests.json
│   ├── checkpoints/
│   └── tickets/
│       ├── _index.json
│       ├── TK-<id>.md         the spec
│       ├── TK-<id>-submit.md  dev submission
│       ├── TK-<id>-review.md  QA / reviewer verdict
│       └── closed/

Everything is plain text or JSON. You can cat your way through the project’s full history. No vector DB lock-in, no opaque embeddings — just files an audit can read.

Current status (v4.0.4, August 2026)

The current local setup is built around one central On Board checkout and one project-selected memory folder:

memory_onboard is the primary start call for agents and returns compact current context.
memory_wait_for_event turns the board push-capable: agents park, wake on peer actions, and close reject/retry loops with zero human relay (see the A2A section).
memory_doctor checks setup and data integrity.
setup-project.sh generates project MCP config, rules, startup hooks, and a dashboard launcher.
Linked-project registry tracks which projects point at the central checkout, so updates can refresh known projects without scanning the machine.
Runtime startup uses python3 onboard_server.py; the launcher normally execs .venv/bin/python server.py and only falls back to uv sync --inexact if .venv is missing.
Startup hooks return a small read-only briefing. End-turn/Stop hooks are not installed by default because current clients can run them too often.
The dashboard is local and read-only.

Full CHANGELOG: CHANGELOG.md.

License

Apache-2.0. Free to use, fork, modify, redistribute, build commercial products on. No restrictions on use.

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