mcp-server

Python MCP server for local interactions with the QuantConnect API.

Available Tools (14)

Tools provided by this Server	Short Description
read_account	Read the organization account status.
create_project	Create a new project in your default organization.
read_project	List the details of a project.
list_projects	List the details of all projects.
update_project	Update a project's name or description.
delete_project	Delete a project.
create_project_collaborator	Add a collaborator to a project.
read_project_collaborators	List all collaborators on a project.
update_project_collaborator	Update collaborator information in a project.
delete_project_collaborator	Remove a collaborator from a project.
read_project_nodes	Read the available and selected nodes of a project.
update_project_nodes	Update the active state of the given nodes to true.
create_compile	Asynchronously create a compile job request for a project.
read_compile	Read a compile packet job result.

Configuration Examples

To connect local MCP clients (like Claude Desktop) to the QC MCP Server, follow these steps:

1. Install Docker Desktop and Claude Desktop.
2. Clone this repository to your local machine.
3. In a terminal, navigate to the project and then run docker build -t mcp-server ..
4. Add the following JSON to your configuration file:

{
  "mcpServers": {
    "quantconnect": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e", "QUANTCONNECT_USER_ID",
        "-e", "QUANTCONNECT_API_TOKEN",
        "--name",
        "quantconnect-mcp-server",
        "mcp-server"
      ],
      "env": {
        "QUANTCONNECT_USER_ID": "<your_user_id>",
        "QUANTCONNECT_API_TOKEN": "<your_api_token"
      }
    }
  }
}

5. Open Claude Desktop.

Debugging

Logs

To log to the mcp-server-quantconnect.log file, import sys and then print("Hello world", file=sys.stderr).

Inspector

To start the inspector, run npx @modelcontextprotocol/inspector uv run src/main.py. To pass a model to the inspector tool, use JSON (for example, {"name":"My Project","language":"Py"}).