MCP server

The Model Context Protocol server exposes your workspace to AI agents as structured tools: todos and subtodos, lists, labels, comments, dependencies and relations, workflow states, members, and workspace health. A todo filed by an agent is the todo you see in the app — same workspace, same real-time sync.

Everything authenticates with a workspace API key.

Hosted endpoint

Nothing to install — point a Streamable HTTP client at the hosted server with your API key as a Bearer token:

https://api.createtodo.com/mcp
Authorization: Bearer <your-api-key>

For example, in Claude Code:

claude mcp add --transport http createtodo https://api.createtodo.com/mcp \
  --header "Authorization: Bearer $CREATETODO_API_KEY"

Run it locally

Prefer a local process? The same server runs over stdio from npm — add it to any MCP client config:

{
  "mcpServers": {
    "createtodo": {
      "command": "npx",
      "args": ["-y", "@createtodo/mcp"],
      "env": { "API_KEY": "<your-api-key>" }
    }
  }
}

MCP or CLI?

The MCP server is the right fit for chat-centric clients that speak tool calls natively. For coding agents with shell access, the ct CLI is often cheaper: it returns compact JSON the agent can filter before it costs context. They hit the same API — mix freely.