> MCP server.

Parameters use camelCase, but snake_case aliases are also accepted — e.g. mdflow_get_document takes both documentId and document_id.

Claude and the ChatGPT app connect to the hosted server with no token to copy. Add https://mdflow.cz/api/mcp as a custom connector and sign in — MDflow issues the access token for you.

1. 1.In Claude or ChatGPT, open the connector settings and add a custom connector.
2. 2.Paste https://mdflow.cz/api/mcp as the URL and click connect.
3. 3.MDflow's sign-in and consent screen opens. Approve it, and the connector is ready — the mdflow tools appear in the client.

Behind the scenes the client discovers the authorization server from /.well-known/oauth-protected-resource (RFC 9728), registers itself (Dynamic Client Registration), and receives an OAuth access token — nothing is pasted by hand. OAuth is in beta and needs an MDflow Pro account, the same as a Personal Access Token. Prefer a token, or connecting a client that sends its own Authorization header? Use the Personal Access Token setup below.

Clients that send their own Authorization header — Claude Code, Cursor, and the OpenAI Responses API — authenticate the hosted server at https://mdflow.cz/api/mcp with a Personal Access Token instead of the OAuth sign-in above. It runs over the MCP Streamable HTTP transport and is always up to date. Create a Personal Access Token first; it starts with mdf_.

claude mcp add --transport http mdflow https://mdflow.cz/api/mcp \
  --header "Authorization: Bearer mdf_your_token_here"

{
  "mcpServers": {
    "mdflow": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mdflow.cz/api/mcp",
        "--header",
        "Authorization:Bearer mdf_your_token_here"
      ]
    }
  }
}

{
  "mcpServers": {
    "mdflow": {
      "url": "https://mdflow.cz/api/mcp",
      "headers": { "Authorization": "Bearer mdf_your_token_here" }
    }
  }
}

{
  "model": "gpt-5.2",
  "tools": [
    {
      "type": "mcp",
      "server_label": "mdflow",
      "server_url": "https://mdflow.cz/api/mcp",
      "headers": { "Authorization": "Bearer mdf_your_token_here" }
    }
  ],
  "input": "Get information about onboarding from mdflow."
}

For agents: the server is stateless — no session IDs, plain JSON responses, one POST per JSON-RPC message. Rate limit is 60 requests per minute per token; 429 responses carry Retry-After in seconds. The same API is also available as REST — see the API reference and OpenAPI spec.

Prefer a process on your own machine? The local stdio server exposes the same tools and talks to the same API.

• ›Node.js 18+ — the server relies on the built-in fetch.
• ›A terminal with npm.
• ›An MDflow Personal Access Token (created in step 3).

mdflow_get_context is the main agent-facing tool. Given a topic it:

1. 1.Lists folders and documents.
2. 2.Scores folder descriptions highest — they define the intended context for the files they contain.
3. 3.Scores folder names and document titles.
4. 4.Fetches only the selected document bodies.
5. 5.Returns a readable markdown context block plus structured data.

Defaults to 5 documents, each truncated to 12,000 characters. Callers can request up to 10 documents, or between 500 and 50,000 characters per document.

Claude and the ChatGPT app connect to the remote server through their custom-connector pickers with an OAuth sign-in — no token (see above). Clients that attach their own Authorization header — Claude Code, Cursor, VS Code, the OpenAI Responses API, and MCP SDK clients — connect with a Personal Access Token. Claude Desktop can also reach it through the mcp-remote stdio bridge, which requires Node.js. The local server works with clients that can launch a process — Claude Desktop, Codex, Cursor, and similar.