QuantConnect
This QuantConnect MCP server provides AI agents with quantitative finance research capabilities through the QuantConnect platform, offering 40+ tools across nine categories including QuantBook instance management, historical data retrieval, statistical analysis (PCA, cointegration, mean reversion), portfolio optimization with sparse algorithms, universe selection via ETF constituents, alternative data integration, project and file management, backtest execution and analysis, and authentication handling. Built with Python using the FastMCP framework and featuring comprehensive error handling, the implementation supports both local QuantConnect LEAN installations and cloud API access with proper authentication, making it valuable for algorithmic trading research, quantitative analysis workflows, portfolio construction, and building AI-powered financial assistants that need access to professional-grade financial data and analytics tools.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- finance
- Source
- PulseMCP
- Repository
- github.com/taylorwilsdon/quantconnect-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve QuantConnect from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.