SageMath MCP Server

A Model Context Protocol server that gives an LLM a sandboxed mathematical subset of SageMath — symbolic calculus, number theory, linear algebra, ODEs, plotting, combinatorics, graphs, groups, elliptic curves, and more. Each MCP session gets a dedicated Sage worker process, so variables, functions, and assumptions persist across tool calls. It ships 40 MCP tools, one of which — verify_claim — re-checks a stated result through a proof ladder and answers proved / refuted / supported / undecided with its evidence.

Caller code is deny-by-default: the full breadth of Sage mathematics is reachable, but imports, the external CAS interfaces, and the file / display / persistence primitives are not. The policy accepts 98.9% of SageMath's own 432,878 documented doctest examples (3,936 in-scope refusals, every one attributed to a named rule; 99.0% of 433,289 on the passagemath runtime) while refusing the rest — measured on every CI run (see Security).

Full manual: USAGE.md — every tool's parameters and examples, how code is interpreted, and the security model in depth.

Install & run

Recommended — the container image (SageMath is baked in):

docker run --rm \
  --read-only --tmpfs /tmp:rw,size=512m --tmpfs /home/sage/.sage:rw,size=256m \
  --cap-drop ALL --security-opt no-new-privileges --pids-limit 256 --memory 4g \
  -p 127.0.0.1:8314:8314 \
  ghcr.io/xbp-europe/sagemath-mcp:latest

Those flags are the hardening the server expects; the port is published on loopback deliberately — the server executes code and authenticates nobody. docker compose up --build applies the same hardening from one reviewed file. Released images are signed with Cosign and carry SLSA provenance and an SPDX SBOM as registry attestations; the PyPI files carry PEP 740 attestations. DISTRIBUTION.md shows how to verify each.

From PyPI (bring your own Sage runtime):

pip install sagemath-mcp
sagemath-mcp                                             # stdio (default)
sagemath-mcp --transport streamable-http --port 8314    # HTTP on 127.0.0.1

This needs a working SageMath on the host — either sage on your PATH or the sagemath/sagemath Docker image.

A Sage runtime without the 3 GB image (passagemath, optional):

pip install "sagemath-mcp[passagemath]"    # ~1 GB, no Docker, no local Sage build
sagemath-mcp

A pip-installable, modularized fork of SageMath. from sage.all import * and the worker run unmodified; the server detects the runtime at import and loads the matching security artifacts, so the deny-by-default policy is equivalent on both. It is pinned exactly (passagemath-standard==10.8.11) and exercised by its own CI lane — the whole suite plus the doctest-corpus sweep against the pin — so a pin bump is verified end to end before it ships (docs/passagemath_evaluation.md). It is the optional runtime; the monolithic image stays primary, and for untrusted or multi-tenant use run the container regardless of runtime — a pip install has your user's privileges, the container adds OS-level isolation.

On arm64 (Apple silicon, Graviton): the passagemath image. The monolithic image above is published for linux/amd64 only, so on arm64 it runs under emulation. The same server on the passagemath runtime ships as a native linux/amd64 + linux/arm64 image, with the same hardening flags, UID and security policy:

docker run --rm \
  --read-only --tmpfs /tmp:rw,size=512m --tmpfs /home/sage/.sage:rw,size=256m \
  --cap-drop ALL --security-opt no-new-privileges --pids-limit 256 --memory 4g \
  -p 127.0.0.1:8314:8314 \
  ghcr.io/xbp-europe/sagemath-mcp:latest-passagemath

Every release tag has a -passagemath twin (vX.Y.Z-passagemath), each architecture is smoke-tested natively before it is published, and the index is signed and attested like the primary image. It is the optional image on amd64, where the monolithic one stays primary.

Source install, Docker Compose, and the Kubernetes Helm chart are in USAGE.md.

Connect an MCP client

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "sagemath": { "command": "uv", "args": ["run", "sagemath-mcp"] }
  }
}

Claude Code, Codex CLI, Gemini CLI, and HTTP-transport setup are in USAGE.md.

Try it

Prompts a client can run once the server is connected:

• Damped harmonic oscillator — "Solve x'' + 2·x' + 5·x = 0 with x(0)=1, x'(0)=0, then verify the solution satisfies the ODE."
• General relativity — "On the hyperbolic upper half-plane with metric (dx² + dy²)/y², compute the Ricci scalar and confirm it is a constant negative curvature."
• Coupled two-tank system — "Solve the linear ODE system for two mixing tanks, then take the long-term limit of each concentration."

Each builds an object once and explores it across calls — the case for evaluate_sage and its persistent session.

The 40 tools

The math tools use SageMath as the backend; full parameters and examples are in USAGE.md.

Plus HTTP /health and /ready endpoints and 3 MCP resources (session snapshots, monitoring metrics, doc links). Prefer interrupt_sage_session over cancel_sage_session — it stops a computation while keeping the session's variables.

How it works

┌─────────────────────────────────────────────────────────────┐
│  MCP Client (Claude Desktop, Gemini CLI, Codex CLI, ...)    │
└───────────────────────────┬─────────────────────────────────┘
                            │  MCP protocol (stdio or HTTP)
                            ▼
┌─────────────────────────────────────────────────────────────┐
│  app.py + tools/ --- FastMCP 3.x                            │
│  ┌─────────────┐  ┌──────────────┐                          │
│  │ 40 MCP Tools│  │ 3 Resources  │   session.py routes each │
│  └─────────────┘  └──────────────┘   client to its worker   │
└───────────────────────────┬─────────────────────────────────┘
                            ▼   one subprocess per session
┌─────────────────────────────────────────────────────────────┐
│  _sage_worker.py --- allowlist.py + security.py             │
│  AST validation, then exec() in a persistent namespace      │
│  (vars, functions and classes survive across calls)         │
└─────────────────────────────────────────────────────────────┘

Request flow: MCP client → a tool in tools/ → SageSessionManager.get_or_create() → SageSession.evaluate() → JSON request to the _sage_worker.py subprocess → AST validation → exec() in the persistent namespace → JSON response.

• Process isolation — each session runs Sage in its own subprocess; a crash or timeout in one cannot affect another.
• Stateful sessions — variables, functions, and assumptions persist across calls, enabling multi-step workflows.
• Deny-by-default — a name is refused unless the generated allowlist offers it or the caller's own code bound it. A helper a future SageMath adds is refused until someone reviews it, rather than reachable the day it lands.

Security

The AST validator is defence in depth against accidents and casual misuse — it is not a boundary against determined adversarial code. The container is the security boundary. The server has no authentication, so every default is loopback: --host defaults to 127.0.0.1, the default transport is stdio, and Compose / Helm keep the endpoint off the network. Put something that authenticates in front of it before exposing it.

What the policy enforces: an allowlist (caller code may read only a name the server offers or the caller itself bound); no imports by default; eval / exec / compile and runtime string evaluation blocked; dunder access blocked; the external CAS interfaces and every file / network / persistence primitive removed from the namespace, by provenance rather than by name. The container adds a read-only root, dropped capabilities, no-new-privileges, and fork / memory ceilings.

Full threat model and the complete blocked / allowed tables: SECURITY.md and USAGE.md § Security model.

Docs & more

• USAGE.md — the full manual: every tool, how code is interpreted, deployment, and the security model.
• docs/mcp_quickstart.md — a first-session walk-through.
• CHANGELOG.md · ROADMAP.md · CONTRIBUTING.md · SECURITY.md · SUPPORT.md — what "supported" means, release cadence, where to ask.

Requirements

Python 3.12+ and a SageMath runtime (the container image bundles SageMath 10.9; otherwise sage on PATH, or the [passagemath] extra). Built on FastMCP 3.x.

Contributing

Issues and pull requests welcome — see CONTRIBUTING.md. Run make lint and make test before pushing (git config core.hooksPath .githooks wires the pre-push check). Roadmap and open work: ROADMAP.md. Questions go to GitHub Discussions; SUPPORT.md says what to expect.

Citing

If this server is part of published work, cite it via CITATION.cff — GitHub renders it as Cite this repository in the sidebar, with APA and BibTeX. Cite SageMath itself as well; it does the mathematics.

License

MIT — see LICENSE. SageMath itself is GPL-2.0-or-later and is used as a separate runtime; no SageMath source is redistributed in this repository.