agency-os is an open-source tool that turns Notion into an orchestration layer for AI agents, allowing users to plan tasks, approve task trees, and dispatch agents via MCP. It supports model routing and dependency resolution, and works with Claude Code, Cursor, Cline, and other MCP-capable agents.
What if your Notion board was the thing that actually dispatched work to agents, not just tracked it? That is what agency-os does. It is a Claude Code plugin (also works with Cursor, Cline, Continue, and any MCP-capable agent) that turns Notion into an orchestration layer: a place where you plan with an agent, approve a task tree, and then agents pick up rows marked for execution, complete them in dependency order, and write result links back to the board. The loop in practice: 1. You describe an idea. The agent asks clarifying questions, breaks it into tasks and subtasks, sets dependencies on the Notion rows. 2. You approve. Nothing runs without explicit approval. 3. Tasks marked Exec=Agent get dispatched. Agents run in parallel where possible, sequentially where there are dependencies. Each one closes its row with a result link when done. The Notion board is the source of truth throughout. There is no separate database, no config file to sync, no UI to keep open. The agent reads the board, writes to the board, and you see everything in one place. **Why Notion as the dispatch layer?** A few reasons this works better than a YAML task list or a chat thread: * The board is human-readable and human-editable. You can add a task by typing in Notion, and the agent sees it on the next run. * Dependencies are first-class. The agent resolves the DAG at dispatch time, stages tasks, and blocks a child if its parent did not close Done. * Model routing is built in. Mechanical work (form fills, log-and-close tasks, directory submissions) runs on fast cheap models. Substantive drafting and reasoning goes to bigger ones. You configure which tier handles which kind of work at init time. On typical workloads this cuts token spend 5-10x versus routing everything through a flagship model. **The MCP angle** The whole thing runs through MCP. Notion connectivity is via the Notion MCP server. The skill spec itself (`.claude/skills/agency-os/SKILL.md`) is plain readable markdown that any MCP-capable harness can load. Cursor, Cline, and generic MCP agents all work; the README has harness-specific setup guides. **Honest dependency note** The planning and execution layer uses Claude via the Anthropic API. There is no local-model path yet. The skill spec is model-agnostic in principle - it is just instructions - but the current integrations assume an Anthropic-compatible endpoint. If you are running fully local, this is not ready for you yet. Flagging it rather than burying it. MIT licensed. No telemetry, no call-home. Your Notion data stays in your workspace under your own API token. Happy to answer questions about the architecture, the dependency resolution, or the model routing config.
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