What features does QuantConnect MCP server provide?

Q: What features does QuantConnect MCP server provide?

Official MCP server implementation: The server is the official QuantConnect MCP implementation, maintained by the QuantConnect team, with guidance to securely handle code and API tokens.. Dockerized, cross-platform deployment: Delivered as a Docker image (quantconnect/mcp-server) and designed for cross-platform use, with explicit guidance for linux/amd64 and linux/arm64 platforms.. Simple client integration workflow: Provides a guided process to connect local MCP clients (like Claude Desktop) to the QC MCP Server, including configuration steps and platform considerations.. Extensive MCP toolset for project lifecycle: Offers a wide range of tools to manage projects, files, compilations, backtests, optimizations, and Lean versions, enabling end-to-end automation.. Live trading deployment management: Supports creating, reading, listing, stopping, liquidating, and commanding live trading algorithms, along with live chart, logs, portfolio, and orders access.. Collaboration and access control: Includes tools to manage project collaborators and lock projects to coordinate editing and deployment workflows.. Object Store and file management: Provides object store interactions, including uploading, listing, reading properties, and downloading files.. Diagnostics and versioning tooling: Includes server/version queries and code-quality tools (read_mcp_server_version, read_latest_mcp_server_version, check_initialization_errors, complete_code, etc.) to aid debugging and maintenance.

QuantConnect MCP Server 2025: Features & Setup Guide

Overview

The QuantConnect MCP Server is the official bridge that allows AI agents (such as Claude and other OpenAI-based clients) to interact with QuantConnect's cloud platform. It enables AIs to perform tasks on your behalf via the MCP API, including updating projects, writing strategies, running backtests, and deploying strategies to production live-trading. This is the OFFICIAL implementation maintained by the QuantConnect team, recommended to ensure security of code and API tokens. The server is tested and dockerized for easy cross-platform deployment. It supports multi-platform operation (linux/amd64 for standard CPUs and linux/arm64 for ARM chips like Apple Silicon). Getting started involves connecting local MCP clients (e.g., Claude Desktop) to the QC MCP Server by running the official docker image and configuring the claude_desktop_config.json with a quantconnect mcpServers entry. The MCP server exposes a rich set of tools to manage projects, backtests, optimizations, live algorithms, file storage, and more, enabling comprehensive automation of QuantConnect workflows from AI agents.

Features

Official MCP server implementation

The server is the official QuantConnect MCP implementation, maintained by the QuantConnect team, with guidance to securely handle code and API tokens.

Dockerized, cross-platform deployment

Delivered as a Docker image (quantconnect/mcp-server) and designed for cross-platform use, with explicit guidance for linux/amd64 and linux/arm64 platforms.

Simple client integration workflow

Provides a guided process to connect local MCP clients (like Claude Desktop) to the QC MCP Server, including configuration steps and platform considerations.

Extensive MCP toolset for project lifecycle

Offers a wide range of tools to manage projects, files, compilations, backtests, optimizations, and Lean versions, enabling end-to-end automation.

Live trading deployment management

Supports creating, reading, listing, stopping, liquidating, and commanding live trading algorithms, along with live chart, logs, portfolio, and orders access.

Collaboration and access control

Includes tools to manage project collaborators and lock projects to coordinate editing and deployment workflows.

Object Store and file management

Provides object store interactions, including uploading, listing, reading properties, and downloading files.

Diagnostics and versioning tooling

Includes server/version queries and code-quality tools (read_mcp_server_version, read_latest_mcp_server_version, check_initialization_errors, complete_code, etc.) to aid debugging and maintenance.