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mcp-sympy

MCP Tool

daedalus/mcp-sympy

MCP server that exposes SymPy's symbolic mathematics functionality

Install

$ npx loaditout add daedalus/mcp-sympy

Platform-specific configuration:

.claude/settings.json
{
  "mcpServers": {
    "mcp-sympy": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-sympy"
      ]
    }
  }
}

Add the config above to .claude/settings.json under the mcpServers key.

About

mcp-sympy

> MCP server that exposes SymPy's symbolic mathematics functionality

[](https://pypi.org/project/mcp-sympy/) [](https://pypi.org/project/mcp-sympy/) [](https://codecov.io/gh/daedalus/mcp-sympy) [](https://github.com/astral-sh/ruff)

Install
pip install mcp-sympy
MCP Server

mcp-name: io.github.daedalus/mcp-sympy

Usage
As MCP Server

Configure in your MCP client:

{
  "mcpServers": {
    "mcp-sympy": {
      "command": "mcp-sympy",
      "env": {}
    }
  }
}
Python API
from mcp_sympy import tools

# Simplify expressions
result = tools.sympy_simplify("sin(x)**2 + cos(x)**2")
print(result)  # "1"

# Solve equations
result = tools.sympy_solve("x**2 - 4", "x")
print(result)  # "[2, -2]"

# Differentiate
result = tools.sympy_diff("x**2", "x")
print(result)  # "2*x"

# Integrate
result = tools.sympy_integrate("x**2", "x")
print(result)  # "x**3/3"

# Create matrices
result = tools.sympy_matrix("1,2; 3,4")
print(result)  # "Matrix([[1, 2], [3, 4]])"

# Number theory
result = tools.sympy_isprime("7")
print(result)  # "True"
Available Tools

The MCP server exposes comprehensive SymPy functionality including:

  • Symbolic Expressions: symbols, sympify, simplify, expand, factor
  • Calculus: diff, integrate, limit, series, Derivative, Integral
  • Solving: solve, solveset, nsolve, diophantine, dsolve
  • Matrices: Matrix operations, inverse, determinant, eigenvalues
  • Trigonometry: sin, cos, tan, and their inverses
  • Special Functions: gamma, zeta, erf, fibonacci, etc.
  • Number Theory: isprime, prime, gcd, lcm, totient
  • Sets: FiniteSet, Interval, Union, Intersectio

Tags

mcpnumber-theorysymbolic-computationsympy

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Quality Signals

0
Installs
Last updated18 days ago
Security: AMCP ConfigREADME

Safety

Risk Levelmedium
Data Access
read
Network Accessnone

Details

Sourcegithub-crawl
Last commit3/29/2026
View on GitHub→

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