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mma-mcp

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WARNING

This project is deprecated and no longer maintained. The code is kept on GitHub for reference only.

1. Wolfram 15 ships an official MCP server. Mathematica / Wolfram 15 includes the Wolfram/AgentTools paclet, which starts a local stdio MCP server exposing WolframLanguageEvaluator (with per-call timeConstraint, persistent session, and a sandboxed Method -> "Local" mode), WolframContext, notebook read/write, CodeInspector, TestReport and more. For local use this covers most of what mma-mcp was built for — and it does it inside the kernel, rather than through an external wrapper. See the official documentation for usage.

2. The MCP protocol and SDK have moved on. This project targets the v1 Python SDK, including private APIs such as mcp._mcp_server and a hand-written stdio transport, and declares its dependency as mcp[cli]>=1.0 with no upper bound. Now that mcp 2.x is the default install, a fresh install is likely to fail at import time. The embedded OAuth 2.1 server and the session handling in particular no longer match the current MCP authorization model.

3. Security caveat if you run it anyway. The capability-group JSON files are generated locally and are gitignored. If mma-mcp setup has not been run successfully, the default blacklist resolves to an empty set and the expression filter blocks nothing at all — including Run, file I/O and networking. Never point this at untrusted input in that state.

What's next: we are building a separate, much smaller tool focused on reaching your own workstation's Mathematica / Wolfram Engine from a phone, via Claude or ChatGPT over HTTPS. Stay tuned.

A Model Context Protocol (MCP) server that wraps a local Wolfram Engine, enabling AI assistants (Claude, ChatGPT, etc.) to perform symbolic math, numerical analysis, and data visualization via Wolfram Language.

Disclaimer: This is an unofficial, independent, personal project. It is not affiliated with, sponsored by, endorsed by, or certified by Wolfram Research, Inc. "Wolfram", "Wolfram Language", "Wolfram Engine", "Mathematica", and related marks are trademarks of Wolfram Research.

This software does not include any Wolfram Engine / Mathematica binaries, activation keys, license files, or other proprietary materials. Users must independently obtain and properly license their own copy of the Wolfram Engine or Mathematica in accordance with Wolfram's licensing terms.

The sole purpose of this project is to allow a licensed individual to invoke their own, locally-installed Wolfram kernel through AI assistants on their own machine, within the scope permitted by their license. Redistribution of Wolfram Engine access to third parties is not an intended use case and may violate Wolfram's licensing terms.

Features

  • MCP Tools: evaluate (text) and evaluate_image (PNG, experimental) — all Wolfram Language capabilities through two universal tools

  • Transports: stdio (local) and Streamable HTTP

  • Security: Pre-kernel expression filtering with blacklist/whitelist modes and 29 capability groups

  • Client RBAC: Per-client credentials, per-role tool and security policy control — for isolating different AI clients on the same machine

  • OAuth 2.1: Authorization server for web-based MCP clients (Claude.ai, ChatGPT)

  • Config-driven: Single TOML file controls all behavior

Related MCP server: MCP Mathematics

Prerequisites

Quick Start

# Clone and install
git clone https://github.com/siqiliu-tsinghua/mma-mcp.git
cd mma-mcp
uv sync

# Graphics export dependencies (headless servers only — desktops already have these)
sudo apt-get install -y libfontconfig1 libgl1 libasound2t64 libxkbcommon0 libegl1

# Generate default config
uv run mma-mcp init

# Generate security group files (requires Wolfram kernel, ~1 min)
uv run mma-mcp setup

# Start server (stdio, for local MCP clients)
uv run mma-mcp serve

Client Configuration

Claude Code / VS Code (stdio)

Add to your .mcp.json:

{
  "mcpServers": {
    "mma-mcp": {
      "command": "uv",
      "args": ["--directory", "/path/to/mma-mcp", "run", "mma-mcp"]
    }
  }
}

Claude Desktop (stdio)

Add to your claude_desktop_config.json (Settings -> Developer -> Edit Config):

{
  "mcpServers": {
    "mma-mcp": {
      "command": "/path/to/mma-mcp/.venv/bin/mma-mcp"
    }
  }
}

On macOS/Linux, find the config at ~/Library/Application Support/Claude/claude_desktop_config.json or ~/.config/Claude/claude_desktop_config.json.

HTTP Transport

uv run mma-mcp serve --transport http --host 127.0.0.1 --port 8000

Configuration

All settings live in mma_mcp.toml (or pyproject.toml under [tool.mma-mcp]).

uv run mma-mcp init  # generates mma_mcp.toml with comments

Key sections:

Section

Description

[kernel]

Wolfram kernel path, timeout, output format

[server]

Transport mode, host, port

[security]

Blacklist/whitelist mode, capability groups

[tools]

Which MCP tools to expose

[tls]

Domain and DNS provider for HTTPS (Caddy)

[auth]

Client identity and role-based access control

Security

Expressions are filtered before reaching the Wolfram kernel. Symbols are extracted via regex and checked against the active policy.

Blacklist mode (default): blocks dangerous groups (system_exec, file I/O, networking, dynamic eval).

Whitelist mode: only allows symbols from explicitly enabled groups.

29 capability groups (22 safe + 7 dangerous) cover ~6000 Wolfram Language symbols. Regenerate from your local kernel:

uv run mma-mcp setup          # required after cloning (generates from your local kernel)
uv run mma-mcp setup --force   # force regeneration (e.g., after Wolfram Engine upgrade)

Client Identity & Roles

When using HTTP transport, you can configure per-client credentials and roles to isolate different AI clients (e.g., Claude and ChatGPT) connecting to the same kernel:

# Generate password hash
uv run mma-mcp hash-password

# Generate TOML snippet for a new client
uv run mma-mcp add-client alice --role admin

Each client is bound to a role that controls which tools it can access, which Wolfram symbols it can use, and resource limits (timeout, result size). Concurrent clients are isolated via a kernel worker pool — each tool call runs in an exclusive kernel process with a temporary WL context.

See the [auth] section in mma_mcp.toml for configuration details.

Development

# Run tests
uv run pytest tests/ -v

# Inspect MCP tools interactively
uv run mcp dev src/mma_mcp/server.py

CLI Commands

Command

Description

mma-mcp serve

Start the MCP server (default)

mma-mcp init

Generate default mma_mcp.toml

mma-mcp setup

Generate security group JSONs from local kernel

mma-mcp caddyfile

Generate Caddyfile for HTTPS

mma-mcp hash-password

Hash a password for config

mma-mcp add-client

Generate TOML snippet for a new AI client

Client Compatibility

Client

Long computations

Notes

Claude.ai

✔ Supported

Sends progressToken; server heartbeat keeps connection alive

ChatGPT

✘ May timeout

Does not send progressToken; has a hard timeout (~60s) independent of server heartbeat

Claude Desktop / Claude Code

Not tested

Local stdio transport

License

MIT — applies only to the code in this repository. Use of Wolfram Engine / Mathematica is governed by Wolfram Research's own license terms.

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