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step-by-step-math

by gonzavh17
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Python
Hybrid

step-by-step-math

MCP server that solves math step by step with a symbolic engine and renders each step on a visual whiteboard.

Status: work in progress. Right now it exposes three tools backed by SymPy: differentiate, integrate and verify_antiderivative. Step-by-step solutions and the whiteboard are coming next.

Requirements

  • Python 3.12+

  • uv

Related MCP server: Symath-MCP

Run locally

uv sync
uv run pytest                 # run the tests
uv run step-by-step-math      # start the MCP server over stdio

Try it with MCP Inspector

npx @modelcontextprotocol/inspector uv --directory /path/to/step-by-step-math run step-by-step-math

Use it from Claude Code

claude mcp add step-by-step-math -- uv --directory /path/to/step-by-step-math run step-by-step-math

Tools

Tool

Input

Output

differentiate

expression, variable (default x)

result as text and LaTeX

integrate

expression, variable, optional lower / upper (0, pi/2, oo, ...)

antiderivative + C or value, LaTeX, method used, verification; improper integrals and divergence are detected

verify_antiderivative

integrand, antiderivative, variable

verified, inconclusive or incorrect (with the difference)

Expressions use SymPy syntax (x**2, exp(x), sin(x), log(x)); sen, tg and ln are accepted too.

Configuration

Each computation runs in a separate process that is killed if it exceeds its limits.

Variable

Default

Meaning

STEP_BY_STEP_MATH_TIMEOUT

10

seconds per computation

STEP_BY_STEP_MATH_MEMORY_MB

512

memory limit per computation (0 = no limit)

STEP_BY_STEP_MATH_MAX_CONCURRENT

2

computations running at the same time

STEP_BY_STEP_MATH_TRANSPORT

stdio

stdio or http

STEP_BY_STEP_MATH_PATH_TOKEN

—

required with http: secret path segment, at least 32 URL-safe characters

PORT

8000

HTTP port (set by Railway)

Deploy

The repo includes a Dockerfile (uv, python:3.14-slim) that starts the server over streamable HTTP:

  • MCP endpoint: https://<your-domain>/mcp/<STEP_BY_STEP_MATH_PATH_TOKEN>

  • Health check: GET /health

The full MCP URL is the secret. Custom connectors in claude.ai and ChatGPT cannot reliably send a fixed auth header, so the server is protected by an unguessable path segment instead. Anyone with the URL can use the server: don't share it, and rotate the token (redeploy with a new value) if it leaks. Any other path under /mcp returns 404, and request paths are not logged.

Run the image locally:

podman build -t step-by-step-math .   # or docker
TOKEN=$(python3 -c "import secrets; print(secrets.token_urlsafe(32))")
podman run --rm -p 8000:8000 -e STEP_BY_STEP_MATH_PATH_TOKEN="$TOKEN" step-by-step-math
npx @modelcontextprotocol/inspector --cli "http://127.0.0.1:8000/mcp/$TOKEN" --transport http --method tools/list

On Railway: deploy the repo (the Dockerfile is detected automatically), set STEP_BY_STEP_MATH_PATH_TOKEN, generate a public domain and set the health check path to /health. Railway sets PORT.

License

MIT

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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