QuantConnect/mcp-server

Overview

This is an official Python server that implements the Model Context Protocol for local interactions with the QuantConnect API. It allows AI agents or tools to access QuantConnect’s algorithmic trading platform through a standardized interface.

Best for

Best for
Developers building AI agents that need direct, local access to QuantConnect’s algorithmic trading capabilities.

Use cases

• Building AI agents that can execute trades and retrieve market data via QuantConnect
• Integrating QuantConnect account management into custom development workflows
• Automating algorithmic trading strategies with context-aware model interactions

How to use

Tools exposed

• read_account
• create_project
• read_project
• list_projects
• update_project
• delete_project
• create_project_collaborator
• read_project_collaborators
• update_project_collaborator
• delete_project_collaborator
• lock_project_with_collaborators
• read_project_nodes
• update_project_nodes
• create_compile
• read_compile
• create_file
• read_file
• update_file_name
• update_file_contents
• patch_file

Tested with

Claude Desktop, VS Code, ChatGPT

Example client config

{\n  "mcpServers": {\n    "quantconnect": {\n      "command": "docker",\n      "args": [\n        "run",\n        "-i",\n        "--rm",\n        "-e", "QUANTCONNECT_USER_ID",\n        "-e", "QUANTCONNECT_API_TOKEN",\n        "-e", "AGENT_NAME",\n        "--platform", "<your_platform>",\n        "quantconnect/mcp-server"\n      ],\n      "env": {\n        "QUANTCONNECT_USER_ID": "<your_user_id>",\n        "QUANTCONNECT_API_TOKEN": "<your_api_token>",\n        "AGENT_NAME": "MCP Server"\n      }\n    }\n  }\n}

Notes

This is an official Python server that implements the Model Context Protocol for local interactions with the QuantConnect API. It allows AI agents or tools to access QuantConnect’s algorithmic trading platform through a standardized interface.

74 stars on GitHub. Last updated 2026-05-07. Licensed Apache-2.0.

Use cases

• Building AI agents that can execute trades and retrieve market data via QuantConnect
• Integrating QuantConnect account management into custom development workflows
• Automating algorithmic trading strategies with context-aware model interactions

Pros

• Official tool from QuantConnect, ensuring API compatibility
• Uses the Model Context Protocol for standardized agent integration
• Pure Python implementation, easy to extend or embed

Cons

• Relatively small community (74 stars) may limit support and examples
• Requires a QuantConnect account and API key to function
• Python only, not available for other languages

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.