FrameOn MCP

MCP server for agentic project management. Tasks, documents, decisions and time in one shared team context, reachable by an AI agent over the Model Context Protocol.

This repository holds the public surface of that server: the protocol types, the guide the server serves to connected clients, the skill playbooks, and the published manifest. The server itself is hosted — you do not run it.

Endpoint	https://api.frameonlab.com/api/v1/mcp
Transport	streamable-http
Auth	OAuth 2.1 — Dynamic Client Registration, PKCE (S256) required
Tools	20 (13 read-only, 7 write) — see docs/tools.md
Registry	com.frameonlab/frameon
Docs	https://app.frameonlab.com/mcp

Why this exists

An AI assistant asked to help with a project normally works from whatever got pasted into the chat. It cannot see what was decided three weeks ago, which constraint someone stated in a meeting, or who is already on the task. So it guesses, confidently, and a human spends the afternoon correcting it.

FrameOn exposes the project itself: the task tree, the wiki where decisions live, a separate project memory holding conventions and traps, the team, the alerts and the time log. The agent reads the real state, writes back what it did, and the next agent — on another machine, in another client — finds it there.

Connect

Claude Code

claude mcp add --transport http frameon https://api.frameonlab.com/api/v1/mcp

Claude Desktop, Cursor, and other mcpServers clients

{
  "mcpServers": {
    "frameon": {
      "type": "http",
      "url": "https://api.frameonlab.com/api/v1/mcp"
    }
  }
}

ChatGPT

Add a connector pointing at the same URL. The OAuth flow runs in the browser; no key is pasted anywhere.

There is no API key in any of these. The first call opens an authorisation screen, a human approves the workspace, and the client stores a token it rotates on its own. A Personal Access Token also works, as Authorization: Bearer …, for scripted use where no browser exists.

More, including a per-client walkthrough: https://app.frameonlab.com/mcp

What the agent gets

Connect and call frameon://guide. The server hands back a written briefing — what FrameOn is, which tool answers which question, the traps that cost a round-trip, and, just as importantly, what FrameOn has that the agent does not: the Gantt, the approval step on timesheets, the financial reports. A tool that refuses to say where its edges are gets improvised around, badly.

Scope of this repository

Path	What it is
src/mcp.types.ts	JSON-RPC 2.0 envelope types and the protocol versions the server echoes
src/mcp-guide.ts	the text served at frameon://guide, plus the prompt specs
src/mcp-skills.ts	the skill playbooks behind list_skills / get_skill
server.json	the manifest published to the MCP registry
docs/tools.md	the 20 tools, with the descriptions the server advertises
examples/	client configuration, ready to paste

The service implementation, the database and the tenant layer are not here and are not open source. What is here is what a client talks to and what an agent reads — enough to know exactly what you are connecting to before you connect.

Security

The endpoint is multi-tenant and every query filters by tenant. A credential reaches the projects its role reaches and nothing else; tenant_id never appears in a tool response. Write tools are gated per call, on the scope and the role carried by the credential — never on anything sent in the request body.

Found something that looks wrong? seguranca@frameonlab.com. Please do not open a public issue for a suspected vulnerability.

Licence

MIT — see LICENSE.