Quantcontext MCP Server

@zomma-dev

Basic information

About Quantcontext MCP Server

QuantContext is an MCP server that gives AI agents real quant computation for better trading: stock screening, strategy backtesting, and factor analysis.

Quantcontext MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Quantcontext MCP Server tools

Filter S&P 500, Nasdaq 100, or Russell 2000 by fundamentals, momentum, quality, technical signals, or a multi-factor blend. Returns ranked candidates.

Test a strategy over history with a rebalance-loop engine. Returns CAGR, Sharpe, max drawdown, equity curve, and trade log.

Decompose strategy returns into Fama-French factors (market, size, value, momentum). Returns alpha with t-statistic, factor loadings, and R-squared.

Overview

What is Quantcontext Mcp Server?

QuantContext is an MCP server that gives AI agents real quant computation for better trading: stock screening, strategy backtesting, and factor analysis.

How to use Quantcontext Mcp Server?

Follow the repository README to install the server and add its MCP configuration to your client.

Key features of Quantcontext Mcp Server

Docs — full reference, examples, methodology
PyPI

Use cases of Quantcontext Mcp Server

Connect an MCP-compatible client to this repository's service.
Review the README-backed setup before enabling it in production.

Frequently asked questions

Where is the source code for Quantcontext Mcp Server?

The source code is linked from the repository URL on this page.

Does Quantcontext Mcp Server include a standard MCP config?

If the README contains a parseable MCP configuration block, it is shown in the Config tab.

Comments

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