QuantContext
QuantContext is an MCP server that gives AI agents real quant computation for better trading: stock screening, strategy backtesting, and factor analysis.
What is QuantContext?
QuantContext is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to quantcontext is an mcp server that gives ai agents real quant computation for better trading: stock screening, strategy backtesting, and factor analysis.
QuantContext is an MCP server that gives AI agents real quant computation for better trading: stock screening, strategy backtesting, and factor analysis.
This server falls under the Finance & Fintech category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- QuantContext is an MCP server that gives AI agents real quan
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx quantcontextConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use QuantContext
QuantContext is a Python MCP server that gives AI agents real quantitative computation for equity research and trading. It provides three core tools — stock screening across major indices, historical strategy backtesting with performance metrics, and Fama-French factor analysis — all using free public data sources. No API keys or paid subscriptions are required.
Prerequisites
- Python 3.9 or later installed
- pip package manager
- Claude Desktop or Claude Code
- Internet access to Yahoo Finance and Kenneth French Data Library
Install the quantcontext-mcp package
Install QuantContext from PyPI. This also installs the quantcontext CLI entry point.
pip install quantcontext-mcpVerify the installation
Confirm the CLI is available and the server starts without errors.
quantcontext --helpAdd to Claude Code
Register the QuantContext server with Claude Code using the mcp add command.
claude mcp add quantcontext -- quantcontextConfigure Claude Desktop
Add the server to your Claude Desktop configuration file. No environment variables are needed — the server requires no credentials.
{
"mcpServers": {
"quantcontext": {
"command": "quantcontext"
}
}
}Restart Claude Desktop and verify tools
Restart Claude Desktop. The three QuantContext tools should appear: screen_stocks, backtest_strategy, and factor_analysis.
QuantContext Examples
Client configuration
Minimal Claude Desktop configuration for QuantContext — no API keys required.
{
"mcpServers": {
"quantcontext": {
"command": "quantcontext"
}
}
}Prompts to try
Quantitative research prompts to use with QuantContext in Claude.
- "Screen the S&P 500 for value stocks with PE ratio under 15 and ROE above 12%"
- "Find the top 20% momentum stocks in the Nasdaq 100 over the past 200 days"
- "Backtest a monthly-rebalanced momentum strategy on the S&P 500 over the last 3 years and show CAGR and Sharpe ratio"
- "Run factor analysis on my portfolio returns and show the Fama-French factor loadings"
- "Which Russell 2000 stocks have the highest quality scores?"Troubleshooting QuantContext
'quantcontext' command not found after pip install
The pip install target bin directory may not be in your PATH. Run 'python -m quantcontext' as an alternative, or add the pip bin directory to PATH (e.g., ~/.local/bin on Linux/macOS). In Claude Desktop config, use the full path: 'command': '/Users/you/.local/bin/quantcontext'.
screen_stocks returns an error fetching data for the S&P 500 universe
QuantContext fetches constituent lists from Wikipedia and price data from Yahoo Finance. A network timeout or Wikipedia formatting change may cause failures. Check your internet connection and retry — the data sources are public and occasionally change structure.
backtest_strategy returns NaN for Sharpe ratio
A Sharpe ratio of NaN usually means the strategy had zero or near-zero returns variance over the test period. Try a longer backtest window (e.g., 3-5 years) or a different universe/strategy combination.
Frequently Asked Questions about QuantContext
What is QuantContext?
QuantContext is a Model Context Protocol (MCP) server that quantcontext is an mcp server that gives ai agents real quant computation for better trading: stock screening, strategy backtesting, and factor analysis. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install QuantContext?
Follow the installation instructions on the QuantContext GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with QuantContext?
QuantContext works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is QuantContext free to use?
Yes, QuantContext is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Set Up QuantContext in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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