Sympy MCP is a free Model Context Protocol (MCP) server developed by Sdiehl, built with Python. It functions as a Symbolic Algebra MCP Server, specifically designed to empower Large Language Models (LLMs) to accurately execute symbolic mathematics and computer algebra tasks. This platform aims to overcome typical LLM difficulties with complex symbolic manipulation, connecting LLMs to powerful computational capabilities. It is distributed as source code via Git, installable with the "uv" Python package manager, or as Docker container images.

What does Sympy MCP connect to?

Sympy MCP functions as a specialized Model Context Protocol (MCP) server, primarily designed for establishing connections with Large Language Models (LLMs). It falls under the category of a Symbolic Algebra MCP Server, which enables LLMs to autonomously perform complex symbolic mathematics and various computer algebra operations. The server specifically supports "streamable-http" as its transport protocol, ensuring efficient data exchange. AI clients that have been confirmed compatible with Sympy MCP include Claude Desktop and Cline, directly integrating LLM interactions into its mathematical processing workflow.

Core features and tools

Sympy MCP exposes a powerful subset of SymPy's core symbolic mathematics capabilities, allowing LLMs to perform advanced calculations. These include fundamental operations such as algebraic equation solving, integration, and differentiation across various mathematical contexts. The server further extends to more specialized domains like vector calculus and advanced tensor calculus for general relativity. Moreover, it provides support for both ordinary differential equations and partial differential equations, enabling LLMs to tackle diverse mathematical challenges.

Who is it for?

Sympy MCP is primarily intended for Large Language Models (LLMs) and for users who require LLMs to perform highly accurate symbolic mathematics and computer algebra. It is particularly valuable in scientific and engineering fields where LLMs often struggle with intricate symbolic manipulation, offering a reliable computational backend. The program enhances LLMs' ability to process and solve complex mathematical problems effectively. Skip this if your primary need is not for LLMs to execute symbolic mathematical computations, especially in areas like calculus or equation solving.

How to get started

No credentials are required for authentication when running Sympy MCP. The server supports "streamable-http" as its transport protocol.

Use cases

• Solving differential equations, such as the damped harmonic oscillator, demonstrating its utility in physics and engineering.
• Performing tensor calculus for general relativity, like computing the trace of the Ricci tensor, crucial for advanced theoretical physics.
• Setting up and solving coupled systems of ordinary differential equations, applicable in various modeling and simulation scenarios.

Sympy MCP provides LLMs with essential symbolic mathematics capabilities, addressing a known weakness in complex computation. Its free license and Python foundation make it accessible for enhancing LLM mathematical accuracy. The developer notes a security concern regarding arbitrary code execution when run locally. Try performing tensor calculus for general relativity, like computing the trace of the Ricci tensor.