Deterministic stock screening, backtesting, and factor analysis for AI trading agents
Run one of the commands below, then add the client config underneath.
Pythonuvx quantcontext-mcp
Paste into Claude Desktop, Cursor (mcp.json), VS Code or any MCP client, then restart the client.
mcpServers{
"mcpServers": {
"quantcontext": {
"command": "uvx",
"args": [
"quantcontext-mcp"
]
}
}
}
QuantContext is listed in the Finance & Payments category of the MCPNav directory. It is distributed as Python and can be loaded by any client that speaks the Model Context Protocol.
Typical uses include giving your assistant scoped access to the corresponding service so it can answer questions and take actions with real data instead of guessing. Always review what a server can access before you enable it — see our MCP security guide.
QuantContext is an MCP server by zomma-dev. Deterministic stock screening, backtesting, and factor analysis for AI trading agents
Install it with: uvx quantcontext-mcp. Then add the JSON config to your client's MCP settings and restart the client.
The MCP server itself is free to install. The source is public on https://github.com/zomma-dev/quantcontext-mcp-server. Any third-party API it calls (such as a search or maps API) may require its own key and billing.
Any MCP-compatible client can use it, including Claude Desktop, Cursor, VS Code, Windsurf and custom agents.