scicomp-math-mcp
mcp-name: io.github.andylbrummer/math-mcp
MCP server for symbolic algebra and GPU-accelerated numerical computing.
Overview
This server provides tools for mathematical computation combining symbolic algebra with numerical computing:
- Symbolic mathematics - Equations, simplification, differentiation, integration (via SymPy)
- GPU-accelerated numerics - Fast array operations and linear algebra
- Mathematical transforms - FFT, optimization, root finding
- Linear systems - Solving systems of equations with GPU acceleration
Installation & Usage
# Run directly with uvx (no installation required)
uvx scicomp-math-mcp
# Or install with pip
pip install scicomp-math-mcp
# Then run as a command
scicomp-math-mcp
Available Tools
Symbolic Computation
symbolic_solve- Solve symbolic equationssymbolic_diff- Compute derivativessymbolic_integrate- Compute integralssymbolic_simplify- Simplify expressions
Numerical Computing
create_array- Create arrays with various patternsmatrix_multiply- GPU-accelerated matrix multiplicationsolve_linear_system- Solve Ax = bfft/ifft- Fast Fourier transformsoptimize_function- Function minimizationfind_roots- Find function roots
Configuration
Set the MCP_USE_GPU environment variable to enable GPU acceleration:
MCP_USE_GPU=1 scicomp-math-mcp
Examples
📖 Code Examples
Practical tutorials in EXAMPLES.md:
- Projectile motion with symbolic + numerical computation
- Chemical equilibrium analysis
- Fourier signal analysis
- Circuit analysis with linear systems
- Progressive difficulty (beginner → advanced)
📚 Full Documentation
See the API documentation for complete API reference.
Part of Math-Physics-ML MCP System
Part of a comprehensive system for scientific computing. See the documentation for the complete ecosystem.
Metadata
Release files for scicomp-math-mcp 0.1.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scicomp_math_mcp-0.1.6.tar.gz | 11.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scicomp_math_mcp-0.1.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.5 kB
Release files / scicomp_math_mcp-0.1.6.tar.gz
| Download URL | scicomp_math_mcp-0.1.6.tar.gz |
|---|---|
| Size | 11.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Yes |
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twine/6.1.0 CPython/3.13.7
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Transparency logRelease files / scicomp_math_mcp-0.1.6-py3-none-any.whl
| Download URL | scicomp_math_mcp-0.1.6-py3-none-any.whl |
|---|---|
| Size | 7.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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ccc8a124428d717b1a00748a7f356b5ec515c150e17cf4776775963ec08b2e90
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jan 5, 2026.
Transparency log