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server for AgentPlanner — AI agent orchestration with planning, dependencies, knowledge graphs, and human oversight","maintainers":[{"name":"tagents","email":"michael@talkingagents.com"}],"readme":"# AgentPlanner MCP Server\n\n[![npm](https://img.shields.io/npm/v/agent-planner-mcp)](https://www.npmjs.com/package/agent-planner-mcp)\n[![MCP](https://img.shields.io/badge/MCP-compatible-blue)](https://modelcontextprotocol.io)\n[![MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)\n\nMCP server for [AgentPlanner](https://agentplanner.io) — AI agent orchestration with planning, dependencies, knowledge graphs, and human oversight. Works with Claude Desktop, Claude Code, ChatGPT, Cursor, Windsurf, Cline, and any MCP-compatible client.\n\n## Prerequisites\n\n- An AgentPlanner account at [agentplanner.io](https://agentplanner.io)\n- An API token (Settings > API Tokens in the AgentPlanner UI)\n\n## Setup\n\n### Claude Desktop — one-click install (`.mcpb`)\n\nThe fastest path. Download `agent-planner.mcpb` from the [latest release](https://github.com/TAgents/agent-planner-mcp/releases), double-click it, and Claude Desktop will install the extension and prompt for your AgentPlanner API token. No Node.js setup, no JSON editing.\n\nTo build the bundle yourself:\n\n```bash\nnpm run build:mcpb        # produces agent-planner.mcpb\nnpm run validate:mcpb     # schema-check manifest.json\n```\n\n### Manual config (Claude Desktop, Claude Code, Cursor, etc.)\n\nAdd to your MCP client config (`claude_desktop_config.json`, `.cursor/mcp.json`, etc.):\n\n```json\n{\n  \"mcpServers\": {\n    \"agentplanner\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"agent-planner-mcp\"],\n      \"env\": {\n        \"API_URL\": \"https://agentplanner.io/api\",\n        \"USER_API_TOKEN\": \"your_token_here\"\n      }\n    }\n  }\n}\n```\n\n## Thin local client (v1)\n\nA lightweight CLI loop for task-driven workflows. No MCP client required — useful when an agent (Claude Code, OpenClaw, a script) just needs to read its current task as files and write status back.\n\n### Mental model\n\n- AgentPlanner (the API) is the source of truth.\n- `.agentplanner/` files are a regeneratable cache, written by the CLI for the agent to read.\n- The agent works in the real repo. Status changes flow back via explicit writeback commands. There is no live sync.\n\n> **Running locally?** See [agent-planner/LOCAL_QUICKSTART.md](https://github.com/TAgents/agent-planner/blob/main/LOCAL_QUICKSTART.md) for the 5-minute path to a full local stack you can point this CLI at. Use `--api-url http://localhost:3000` in the `login` step below.\n\n### The loop\n\n```bash\n# 1. Login — saves credentials and auto-selects a default plan\n#    (pass --plan-id to pick one, or it auto-selects if you have exactly one plan)\nnpx agent-planner-mcp login --token <token> --api-url https://agentplanner.io/api [--plan-id <id>]\n#    Localhost variant (after `docker compose -f docker-compose.local.yml up`):\nnpx agent-planner-mcp login --token <token> --api-url http://localhost:3000\n\n# 2. See your task queue\nnpx agent-planner-mcp tasks [--plan-id <id>]\n\n# 3. Pick the next task and pull context (claims it for 30 minutes)\nnpx agent-planner-mcp next [--plan-id <id>]\n#    Force a fresh recommendation even if you have active work:\nnpx agent-planner-mcp next --fresh\n\n# 4. Or pull context for a specific plan/node (no claim, no status change)\nnpx agent-planner-mcp context --plan-id <plan-id> --node-id <node-id>\n#    If a default plan is set, --plan-id can be omitted:\nnpx agent-planner-mcp context --node-id <node-id>\n\n# 5. Explicit writeback. No live sync.\nnpx agent-planner-mcp start                          # claim + mark in_progress\nnpx agent-planner-mcp blocked --message \"Waiting on API decision\"\nnpx agent-planner-mcp done    --message \"Implemented and verified\"\n```\n\n### `next` resolution order\n\n`next` is a smart picker. It resolves in this order:\n\n1. **Resume** — if any task in scope is `in_progress`, pick it. (Source: `resume_in_progress`.)\n2. **Recommend** — call `suggest_next_tasks` (dependency- and RPI-aware) for a fresh pick. (Source: `suggest_next_tasks`.)\n3. **Fallback** — first `not_started` task in your queue. (Source: `my_tasks_fallback`.)\n\n`tasks` is the queue view; `next` is the smart picker; `next --fresh` skips step 1 and forces a fresh recommendation even when active work exists.\n\n### What `start`, `blocked`, `done` actually do\n\n| Command | Status | Claim | Log entry | Learning written to Graphiti |\n|---|---|---|---|---|\n| `start` | `in_progress` | claim (30m TTL) | — | — |\n| `blocked --message ...` | `blocked` | release | `challenge` | — |\n| `done --message ...` | `completed` | release | `progress` | yes (entry_type: `learning`) |\n\nAll hooks are best-effort: claim/release/learning failures do not block the status update. Claim collisions (another agent already holds the lease) are reported but not fatal.\n\n### What `current-task.md` surfaces\n\nBeyond title, description, agent_instructions, and acceptance criteria, the generated `current-task.md` includes BDI signals from the API responses already being fetched:\n\n- **Plan health** — `quality_score`, rationale, `coherence_checked_at` (or \"never\")\n- **Coherence warning** — flagged when `node.coherence_status` is `contradiction_detected` or `stale_beliefs`, with concrete next-step pointers (`check_contradictions`, `recall_knowledge`)\n- **Detected contradictions** — listed when present in the node context\n- **Task mode** — shown when not `free` (RPI awareness for `research`/`plan`/`implement`)\n- **Linked goals**, **relevant knowledge** (top 5), **plan progress snapshot**\n\n### When to use CLI vs MCP vs API skill\n\n| You want… | Use |\n|---|---|\n| Zero-setup local task context for any coding agent (Claude Code, OpenClaw, scripts) | **CLI** (this thin client) |\n| Rich, structured tool access from inside an MCP-aware agent (Claude Desktop, Cursor, etc.) | **MCP** (run `npx agent-planner-mcp` as an MCP server) |\n| Direct programmatic integration from your own service | **API** (REST endpoints; same routes the MCP and CLI use) |\n\nThe CLI is intentionally thin: it covers the read context + writeback loop and nothing else. For decomposition, dependency creation, knowledge graph queries, RPI chains, coherence runs, and goal management, use the MCP server (or the API directly).\n\n## Agent Loop Facade\n\nAgentPlanner API now exposes a narrow `/agent/*` facade for the main autonomous loop. MCP uses this facade when available and falls back to older domain endpoints for self-hosted older APIs.\n\nPrimary mappings:\n\n| MCP tool | Preferred API endpoint |\n|---|---|\n| `briefing` | `GET /agent/briefing` |\n| `claim_next_task` | `POST /agent/work-sessions` |\n| `update_task` with `session_id` + `completed` | `POST /agent/work-sessions/:id/complete` |\n| `update_task` with `session_id` + `blocked` | `POST /agent/work-sessions/:id/block` |\n| `form_intention` | `POST /agent/intentions` when available, with domain-endpoint fallback |\n\nValidation:\n\n```bash\nnpm run validate:mcp-loop\n```\n\nThis checks that the MCP tools route through the facade for briefing, task claim/start, and session completion/blocking.\n\n\n### Claude Desktop\n\nAdd to your `claude_desktop_config.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"agent-planner\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"agent-planner-mcp\"],\n      \"env\": {\n        \"USER_API_TOKEN\": \"your-token\",\n        \"API_URL\": \"https://agentplanner.io/api\"\n      }\n    }\n  }\n}\n```\n\nConfig location: `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) | `%APPDATA%\\Claude\\claude_desktop_config.json` (Windows)\n\n### Claude Code\n\n```bash\nclaude mcp add agent-planner -- npx -y agent-planner-mcp\n```\n\nThen set the env vars `USER_API_TOKEN` and `API_URL=https://agentplanner.io/api`.\n\n### ChatGPT\n\n1. Settings > Apps > Advanced > Developer mode\n2. Add MCP Server > URL: `https://agentplanner.io/mcp`\n3. Auth type: API Key > enter your token from agentplanner.io Settings\n\n### Cursor\n\nAdd to `.cursor/mcp.json` in your project root:\n\n```json\n{\n  \"mcpServers\": {\n    \"agent-planner\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"agent-planner-mcp\"],\n      \"env\": {\n        \"USER_API_TOKEN\": \"your-token\",\n        \"API_URL\": \"https://agentplanner.io/api\"\n      }\n    }\n  }\n}\n```\n\n### Windsurf\n\nAdd to `~/.codeium/windsurf/mcp_config.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"agent-planner\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"agent-planner-mcp\"],\n      \"env\": {\n        \"USER_API_TOKEN\": \"your-token\",\n        \"API_URL\": \"https://agentplanner.io/api\"\n      }\n    }\n  }\n}\n```\n\n### Cline (VS Code)\n\nAdd the same JSON config to your Cline MCP settings in VS Code.\n\n### Any HTTP MCP Client\n\n- Endpoint: `https://agentplanner.io/mcp`\n- Discovery: `https://agentplanner.io/.well-known/mcp.json`\n- Auth header: `Authorization: ApiKey <your-token>`\n- Transport: Streamable HTTP (MCP 2025-03-26)\n\n## Key Features\n\n- **39 BDI-aligned tools** for state, goals, committed actions, and workspace/blueprint management — no CRUD shapes, every tool answers a whole agentic question\n- **Full mutation surface** — agents and humans-via-agents can manage every plan/node/org property, plus workspaces and reusable blueprints, without leaving the conversation; UI is optional inspection\n- **Draft-status seam** — autonomous agent creation lands as drafts surfacing in the dashboard pending queue; human-directed creation defaults to active\n- **Dependency graph** — cycle detection, impact analysis, critical path\n- **Progressive context** — 4-layer context assembly with token budgeting\n- **Knowledge graph** — temporal knowledge via Graphiti (entities, facts, contradictions)\n- **RPI chains** — Research → Plan → Implement task decomposition (one-call shortcut)\n- **Task claims** — TTL-based locking for multi-agent coordination\n- **Organizations** — multi-tenant isolation with member management\n\n## Available Tools (v1.5)\n\n### Beliefs (read state)\n- `briefing` — bundled mission control state in one call\n- `list_plans` — list plans with optional status/visibility/text filters; returns ids, status, last update, and link counts so you can pick a plan without round-tripping `briefing`\n- `task_context` — single task at progressive depth 1-4\n- `goal_state` — single goal deep-dive (details + quality + progress + bottlenecks + gaps)\n- `recall_knowledge` — knowledge graph query (facts, entities, episodes, contradictions)\n- `search` — text search across plans/nodes\n- `plan_analysis` — impact, critical path, bottlenecks, coherence\n\n### Desires (goals)\n- `list_goals` — goals with health rollup\n- `update_goal` — atomic goal update (subsumes link/unlink/achievers)\n- `create_goal` — create a new top-level goal (no parent)\n- `derive_subgoal` — create a sub-goal under an existing parent\n- `record_criterion_progress` — record the latest observed value of a goal's success criterion (e.g. a metric moved 40→72); the write that makes goal attainment real\n\n### Intentions — execution\n- `claim_next_task` — pick + claim + load context (one call)\n- `update_task` — atomic status + log + claim release + learning\n- `release_task` — explicit handoff\n- `queue_decision` — escalate to human (real decision queue)\n- `resolve_decision` — pick up human's answer (atomically materializes any `proposed_subtasks`)\n- `add_learning` — record knowledge episode\n\n### Intentions — creation\n- `form_intention` — create plan + initial tree under a goal, atomically\n- `extend_intention` — add children under an existing parent (lightweight)\n- `propose_research_chain` — RPI triple with 2 blocking edges, in one call\n\n### Intentions — structural mutation\n- `update_plan` — edit any plan property\n- `update_node` — edit any node property except status\n- `move_node` — reparent within plan; cycle-safe\n- `link_intentions` / `unlink_intentions` — manage dependency edges\n- `delete_plan` / `delete_node` — soft-delete via `status='archived'` (recoverable)\n\n### Intentions — sharing & collaboration\n- `share_plan` — atomic visibility + add/remove collaborators\n- `invite_member` — add user to org (by user_id or email)\n- `update_member_role` — owner-only role change\n- `remove_member` — owner/admin removes non-owner member\n\n### Workspaces & Blueprints\n- `list_workspaces` — list workspaces (goal/plan folders) in an organization\n- `create_workspace` — create a new workspace inside an organization (slug auto-generated and de-duped)\n- `list_blueprints` — list blueprints visible to you (owned + public/unlisted), filterable by scope/visibility\n- `save_as_blueprint` — snapshot a live plan as a reusable plan-scope blueprint (structure + agent_instructions + dependencies; excludes run-state)\n- `fork_blueprint` — fork a plan-scope blueprint into a target workspace as a new plan (statuses reset, lineage recorded)\n- `delete_blueprint` — hard-delete a blueprint you own (already-forked plans are unaffected)\n\n### Utility\n- `get_started` — dynamic reference for new agents\n\nSee [SKILL.md](./SKILL.md) for full descriptions, the human-steering scenarios (A/B/C), and `status='draft'` vs `status='active'` guidance.\n\n## LLM Skill Reference\n\nSee **[SKILL.md](./SKILL.md)** for a complete reference designed to be consumed by LLMs. Include it in system prompts or agent configurations to give any LLM full knowledge of how to use AgentPlanner tools effectively.\n\nSee **[AGENT_GUIDE.md](./AGENT_GUIDE.md)** for a quick reference card.\n\n## Transport Modes\n\n### stdio (default)\nFor local use with Claude Desktop, Claude Code, Cursor, Windsurf, Cline:\n```bash\nnpx agent-planner-mcp\n```\n\n### HTTP/SSE\nFor remote access (ChatGPT, cloud deployments, multi-agent systems):\n```bash\nMCP_TRANSPORT=http npx agent-planner-mcp\n# Listens on http://127.0.0.1:3100 (override with PORT)\n```\n\nTransport is Streamable HTTP (MCP 2025-03-26); auth via `Authorization: ApiKey <your-token>`. Production endpoint: `https://agentplanner.io/mcp` (discovery at `https://agentplanner.io/.well-known/mcp.json`).\n\n## Local Development\n\n```bash\ngit clone https://github.com/TAgents/agent-planner-mcp.git\ncd agent-planner-mcp\nnpm install\nnpm run setup    # Interactive setup wizard\nnpm run dev      # Dev server with hot reload\n```\n\n### Environment Variables\n\n| Variable | Description | Default |\n|----------|-------------|---------|\n| `API_URL` | AgentPlanner API URL | `http://localhost:3000` |\n| `USER_API_TOKEN` | API token (required) | — |\n| `MCP_TRANSPORT` | `stdio` or `http` | `stdio` |\n| `PORT` | HTTP mode port | `3100` |\n| `NODE_ENV` | Environment | `production` |\n\n## License\n\nMIT License - see [LICENSE](./LICENSE) for details.\n\n## Support\n\n- [GitHub Issues](https://github.com/TAgents/agent-planner-mcp/issues)\n- [GitHub Releases](https://github.com/TAgents/agent-planner-mcp/releases) for version history and release notes\n","readmeFilename":"README.md"}