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Quantconnect

Quantconnect

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github.com/QuantConnectAI & Agents79Updated 2d ago
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About Quantconnect

QuantConnect Remote MCP Server connects AI assistants to the QuantConnect cloud platform for users developing and running quantitative strategies. Its hosted MCP HTTP endpoint exposes project, strategy, backtesting, optimization, and deployment actions without requiring users to install or run a server.

Key features

  1. 01Hosted MCP HTTP endpoint
  2. 02Authorization for a QuantConnect organization
  3. 03Read and create projects
  4. 04Write strategies and run backtests
  5. 05Optimize parameters and deploy to paper trading

Use cases

  1. 01Let an AI assistant inspect the open project
  2. 02Create and backtest a quantitative strategy in natural language
  3. 03Optimize strategy parameters and summarize results
  4. 04Deploy a strategy to paper trading

MCP support

It exposes QuantConnect platform tools to compatible clients through a remote MCP HTTP server, including project operations, strategy editing, backtesting, and deployment. Organization authorization is required.

#quant-finance#algo-trading#automated-stock-trading

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "quantconnect": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "QUANTCONNECT_USER_ID",
        "-e",
        "QUANTCONNECT_API_TOKEN",
        "-e",
        "AGENT_NAME",
        "quantconnect/mcp-server"
      ],
      "env": {
        "QUANTCONNECT_USER_ID": "<QUANTCONNECT_USER_ID>",
        "QUANTCONNECT_API_TOKEN": "<QUANTCONNECT_API_TOKEN>",
        "AGENT_NAME": "<AGENT_NAME>"
      }
    }
  }
}
Run commanddocker run -i --rm -e QUANTCONNECT_USER_ID -e QUANTCONNECT_API_TOKEN -e AGENT_NAME quantconnect/mcp-server
Environment variables to set
QUANTCONNECT_USER_ID
QUANTCONNECT_API_TOKENSecret
AGENT_NAME

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ociquantconnect/mcp-server

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README
github-header

QuantConnect Remote MCP Server

The QuantConnect Remote MCP Server is the preferred way to connect AI assistants such as Claude to the QuantConnect platform.

There is nothing to install, build, or run. Point your MCP client at the hosted endpoint, authorize it against your QuantConnect organization, and the tools are available immediately.

Note: The remote MCP server requires a paid agent node (A1-1, A4-8, or A16-32) in your organization. The free A-MICRO node cannot connect. See Agent Nodes and Add Nodes.

Quick Start with Claude

The remote server speaks the standard MCP HTTP transport, so any MCP-capable Claude surface can use it. Pick the one you use.

Claude Desktop and claude.ai
  1. Open Settings > Connectors (on the desktop app, File > Settings > Connectors).
  2. Click Add custom connector, give it a name such as QuantConnect, and enter the server URL: 
    https://www.quantconnect.com/api/v2/mcp
  3. Click Connect. Your default browser opens.
  4. Click Continue connecting, select your QuantConnect organization in the Authorize MCP Server form, and click Authorize.
  5. Start a new chat. The QuantConnect tools are listed under the connector and can be enabled per conversation.
Claude Code (terminal)

Register the server once from any terminal:

claude mcp add --transport http quantconnect https://www.quantconnect.com/api/v2/mcp

Then start Claude Code, run /mcp, select quantconnect, and follow the browser authorization flow (Continue connecting > Authorize). Running /mcp again should show the server as connected with its tools listed.

Claude Code in Local Platform (VS Code extension)
  1. Install the Claude Code extension in VS Code.
  2. Create or open a QuantConnect project in Local Platform.
  3. Open the Claude Code panel from the top navigation bar.
  4. Enter /mcp to confirm the QuantConnect MCP Server is connected.
Try it

Once connected, send a simple prompt to verify the tools are working:

Read the open project.

Claude should call the read_open_project tool and describe the project. From there you can ask it to create projects, write and edit strategy files, run backtests, optimize parameters, or deploy to paper trading, all in plain language. For example:

Create a new Python project that buys SPY on the first trading day of each month,
backtest it from 2020 to today, and summarize the results.

Tip for Claude Code users: a CLAUDE.md file in your project or home directory lets you set conventions (Python-first, compile after every edit, position-sizing rules, and so on). The Claude Code docs page includes an example you can copy.

Available Tools

The full, up-to-date list lives in the Key Concepts documentation.

Other Clients

The remote server also works with Copilot, Cursor, Devin Desktop, and any other client that supports the MCP HTTP transport. Setup guides for each are in the MCP Server documentation.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.