MCP server exposing the AI Task Board to any MCP-capable AI agent
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"ai-task-board-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# AI Task Board — MCP Server Exposes the board to **any MCP-capable AI agent** (Claude Code/Desktop, Cursor, Cline, Windsurf, or a custom client — MCP is model-agnostic) as **8 typed tools** mapped 1:1 onto the [Board REST API](../docs/api/openapi.yaml). It is a thin client: it holds one scoped API key (one *actor*) and forwards calls. See the tool contract in [`docs/api/mcp-tools.md`](../docs/api/mcp-tools.md) and per-client wiring + behavioral rules in [`docs/INTEGRATION.md`](../docs/INTEGRATION.md). ## Tools `list_projects` · `get_board` · `list_tasks` · `get_task` (read) · `claim_task` · `create_task` · `update_task` (write) · `add_report` (report) Conflict handling baked in: - `claim_task` on a contested task returns **who holds it and for how long** (never steals it). - `update_task` on a stale `expected_version` returns a `version_conflict` with advice to re-read and retry (never overwrites a human's edit). ## Install & run Published on PyPI — **no clone needed**: ```bash uvx ai-task-board-mcp # or: pip install ai-task-board-mcp && ai-task-board-mcp ``` Config via env: `ATB_API_BASE_URL`, `ATB_API_KEY` (= an actor), `ATB_PROJECT_ID` (optional — the agent calls `list_projects`). For local development from source: `uv venv .venv && uv pip install --python .venv -e ".[dev]"`, then `.venv/bin/python -m atb_mcp.server`. ## Connect to an agent Any MCP client uses the same command + args + env (see [`docs/INTEGRATION.md`](../docs/INTEGRATION.md) for Claude Desktop, Cursor, Windsurf, Cline, and custom clients). Claude Code example: ```bash claude mcp add ai-task-board \ --env ATB_API_BASE_URL=https://board.filbert.games \ --env ATB_API_KEY=<your agent key> \ -- uvx ai-task-board-mcp ``` Or add to a `.mcp.json` / `claude_desktop_config.json`: ```json { "mcpServers": { "ai-task-board": { "command": "uvx", "args": ["ai-task-board-mcp"], "env": { "ATB_API_BASE_URL": "https://board.filbert.games", "ATB_API_K…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.