QuantConnect

The QuantConnect MCP Server is a bridge for AIs (such as Claude and OpenAI o3 Pro) to interact with our cloud platform. When equipped with our MCP, the AI can perform tasks on your behalf through our API such as updating projects, writing strategies, backtesting, and deploying strategies to production live-trading.

What does this entry provide?

QuantConnect is an MCP server entry in ChatHome Skills, sourced from Docker MCP Registry and scored 100/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding QuantConnect to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: Docker MCP Registry
Quality: 100/100
Install method: docker
Repo: Registry only
Repo updated: Oct 27, 2026

Install command

docker run -i --rm mcp/quantconnect

Install method: docker

Review the upstream source before running this command.

GitHub project Homepage

Quality

100

Repo stars

Repo updated

Unknown

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.
Documentation (10) and description quality (10): parsed manifest or SKILL.md frontmatter, and a real description rather than a placeholder.

MCP manifest

{
  "raw": "name: quantconnect\nimage: mcp/quantconnect\ntype: server\nmeta:\n  category: finance\n  tags:\n    - finance\nabout:\n  title: QuantConnect\n  description: The QuantConnect MCP Server is a bridge for AIs (such as Claude and OpenAI o3 Pro) to interact with our cloud platform. When equipped with our MCP, the AI can perform tasks on your behalf through our API such as updating projects, writing strategies, backtesting, and deploying strategies to production live-trading.\n  icon: https://avatars.githubusercontent.com/u/3912814?v=4\nsource:\n  project: https://github.com/QuantConnect/mcp-server\n  branch: master\n  commit: 1f0fa4e4f465bae4cffb2d69eb4701ad1ddff20c\nconfig:\n  description: Configure the connection to QuantConnect MCP Server\n  env:\n    - name: QUANTCONNECT_USER_ID\n      example: \"12345678\"\n      value: \"{{quantconnect.quantconnectuserid}}\"\n    - name: QUANTCONNECT_API_TOKEN\n      example: 61b2c3d4e5f60718293a4b5c6d7e8f90a1b2c3d4e5f60718293a4b5c6d7e8f90\n      value: \"{{quantconnect.quantconnectapitoken}}\"\n    - name: AGENT_NAME\n      example: MCP Server\n      value: MCP Server\n  parameters:\n    type: object\n    properties:\n      quantconnectuserid:\n        type: string\n      quantconnectapitoken:\n        type: string\n      agentname:\n        type: string\n",
  "path": "servers/quantconnect/server.yaml"
}

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