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axiom-advanced-math-mcp

Exact symbolic math for LLMs: integrals, equations, matrices, and claim verification via Giac/Xcas. MCP server + CLI.

Install / Use

claude mcp add tufantunc -- npx -y github:tufantunc/axiom-advanced-math-mcp

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

80/100

Supported Platforms

Claude Code
Claude Desktop

Our assessment of axiom-advanced-math-mcp

axiom-advanced-math-mcp scores 80/100 on our quality scale, 761st of 949 AI & Machine Learning skills we index.

Its MCP Server is 30 KB long, well organised into 45 sections with 20 code examples: a thorough specification that gives an agent plenty to work with.

It has 3 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
30/30
Structure
20/20
Description
12/15
Adoption
3/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 17 days ago, so axiom-advanced-math-mcp is actively maintained.
  • It is released under GPL-3.0, a copyleft license: you can use it, but modified versions you distribute must carry the same license.
  • Its trust signals score 92/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

axiom-advanced-math-mcp compared with similar skills

All 4 of these similar skills score higher than axiom-advanced-math-mcp; compare them before choosing.

SkillScoreStarsUpdatedFormat
axiom-advanced-math-mcp (this skill)by tufantunc80317d agoMCP Server
claude-memby thedotmack100101.9ktodayCLAUDE.md
Agent-Reachby Panniantong100100.1ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10087.2k8d agoCLAUDE.md
headroomby headroomlabs-ai10076.5ktodayCLAUDE.md

Frequently asked questions

How do I install axiom-advanced-math-mcp?
Run claude mcp add tufantunc -- npx -y github:tufantunc/axiom-advanced-math-mcp. The install tabs above show the steps for each supported agent.
Which AI agents does axiom-advanced-math-mcp work with?
It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
Is axiom-advanced-math-mcp safe to use?
It is GPL-3.0-licensed and scores 92/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is axiom-advanced-math-mcp still maintained?
The repository was last updated 17 days ago, so axiom-advanced-math-mcp is actively maintained.

Axiom — Advanced Math MCP Server

npm License: GPL v3+ Node.js >=20 MCP CI codecov

Exact symbolic and numerical mathematics for LLMs — a real computer algebra system (Giac/Xcas) behind the Model Context Protocol, and behind a shell command. Published as axiom-math.

<!-- Absolute raw URL on purpose. npm rewrites relative README paths to github.com/.../blob/HEAD/..., which serves text/html for a .gif and would render as a broken image on the package page. -->

Axiom catching a wrong derivative, then computing an exact integral

Quick start

As a CLI, straight away:

npx -y axiom-math compute 'integrate(sin(x)^3,x)'   # -cos(x)+cos(x)^3/3
npx -y axiom-math verify 'diff(x^3,x) = 3*x^2'      # exit 0 — it holds

As an MCP server, in any client's config:

{ "command": "npx", "args": ["-y", "axiom-math"] }

As an agent skill — drop in skills/axiom-math/SKILL.md, which teaches an agent the three commands and their exit codes.

Why Axiom?

LLMs often make calculation errors, especially with symbolic math, exact fractions, and multi-step problems. Axiom provides verified, exact results through two layers:

  • math.js — Fast numerical evaluation (arithmetic, trigonometry, matrices)
  • Giac/Xcas WASM — Symbolic computation (calculus, algebra, equation solving)

Benchmark Results (GLM-5.1, May 2026)

| Dataset | Baseline | +MCP | Delta | | ----------------- | -------- | ------- | --------- | | GSM8K (100) | 96.0% | 98.0% | +2.0% | | MATH L3 (50) | 70.0% | 80.0% | +10.0% | | MATH L4 (50) | 50.0% | 62.0% | +12.0% | | MATH L5 (50) | 38.0% | 52.0% | +14.0% | | CAS-quick (60) | 55.0% | 70.0% | +15.0% | | Omni-MATH ≥7 (50) | 0.0% | 0–4% | (ceiling) |

Key insights:

  • Phase 0 grader (LaTeX/Unicode normalization + symbolic equivalence) is the dominant value driver across all datasets
  • CAS-quick lifted from 26.7% (April pre-grader) to 70% (post-grader) — the biggest single jump
  • Omni-MATH ≥7 is at ceiling for current LLM+CAS setups; needs fundamentally different approaches (Lean/Coq, fine-tuning, RAG)

Full results: benchmark/results/ and docs/superpowers/specs/ (per-phase analysis)


Features

Axiom exposes 3 MCP tools. Almost everything flows through compute, a single gateway that parses a CAS-style problem string and routes it to the right internal engine — so callers learn one tool, not dozens.

| Tool | Purpose | | --------- | ------------------------------------------------------------------------------------------------------------------------------------- | | compute | Solve any math problem. Pass a CAS-style string (solve(...), diff(...), det([[...]]), C(10,3), 2+3*sin(pi/4)) or any Giac/Xcas expression. | | verify | Independently check a mathematical claim (identity, solution, or computation) via symbolic and/or numeric methods. | | plot | Render a 2D function graph as an SVG image. |

What compute covers

compute recognizes CAS-style verbs and dispatches across these domains. Anything it doesn't recognize falls through to raw Giac/Xcas evaluation.

| Domain | Verbs / examples | | ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Arithmetic & units | 2+3*sin(pi/4), 100 km/h to m/s | | Equation solving | solve(x^2-4=0, x), csolve(...) (complex), solve_system([x+y=5, x-y=1], [x,y]) | | Calculus | diff, int, limit, taylor, desolve (ODEs of any order, and linear constant-coefficient systems) | | Multivariable calculus | gradient, hessian, jacobian, divergence, curl, partial, iint/iiint (multiple integrals), critical_points, lagrange, tangent_plane, directional_derivative | | Algebra | factor, simplify, expand, partfrac | | Linear algebra | det, inv, eigenvals, eigenvects, rref, rank, tran, ker, qr, lu, cholesky, svd, norm, cond | | Number theory | ifactor, isprime, euler, analyze | | Combinatorics | C(n,k), P(n,k), stirling, bell, catalan, derangements, multinomial | | Probability | binomial, normal, poisson, geometric, hypergeometric, chi_square, student_t, f_distribution, beta, exponential | | Hypothesis testing | t_test (one/two/paired), anova, chi_square_test | | Numerical methods | newton, bisection, secant, romberg, simpson | | 2D geometry | distance, midpoint, slope, area_*, perimeter, circumference, line_intersection, point_line_distance, angle_between_lines | | 3D geometry | distance3d, midpoint3d, dot, cross, vector_norm, angle_vectors, plane_from_points, point_plane_distance, line_plane_intersection, plane_plane_angle, line_line_distance, volume_tetrahedron, volume_sphere, volume_parallelepiped | | Transforms & series | laplace, ilaplace, fourier/fft/ifft, sum, product | | Exact values | to_exact, to_decimal, simplify_fraction | | Regression & sequences | linear_regression/fit, polynomial_regression, sequence (pattern identification) |


Installation

The package is axiom-math on npm. Nothing to install for normal use — npx fetches and caches it:

npx -y axiom-math compute '2+2'

Or install it so the axiom-math command is on your PATH:

npm install -g axiom-math

Node.js >= 20 required. The first run downloads about 3.8 MB (the CAS engine compiled to WebAssembly) and takes a few seconds; later runs come from the npx cache.

From source

For contributors, or to run a modified build:

git clone https://github.com/tufantunc/axiom-advanced-math-mcp.git
cd axiom-advanced-math-mcp
npm install
npm run build

Docker

# Build and run
docker-compose -f docker/docker-compose.yml up -d

# Check logs
docker-compose -f docker/docker-compose.yml logs -f

# Stop
docker-compose -f docker/docker-compose.yml down

Usage

CLI (STDIO Transport)

# Run with stdio transport (default)
npm start

# Development mode
npm run dev

Claude Desktop integration:

// ~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": [
    {
      "name": "axiom-math",
      "command": "npx",
      "args": ["-y", "axiom-math"]
    }
  ]
}

Running from a local checkout instead of npm — point args at the built entry point:

"args": ["/path/to/axiom-advanced-math-mcp/dist/cli.js"]

Command line

The same binary works as a one-shot CLI, so agents can use it as a skill with no MCP configuration. With no arguments it is the MCP server; with a subcommand it runs one computation and exits.

npx -y axiom-math compute 'integrate(sin(x)^3,x)'
npx -y axiom-math compute -q 'solve(x^2-4=0,x)'     # {-2, 2}
npx -y axiom-math verify 'sin(x)^2+cos(x)^2 = 1'    # exit 0 if true
npx -y axiom-math plot 'sin(x)' -o wave.svg
echo 'diff(x^3,x)' | npx -y axiom-math compute -q   # 3*x^2

| Flag | Meaning | | --- | --- | | -q | print one value only, for scripting | | --json | structured output | | --latex | LaTeX-focused text (compute only) | | -h, --help | usage, or usage for a subcommand |

Exit codes: 0 success · 1 tool or usage error · 2 verify checked the claim and it is false.

2 is a mathematical verdict, so a claim that never got checked does not use it: one that fails to parse, that the CAS cannot evaluate, or that has a superscript with more than one reading, exits 1 with nothing on stdout. axiom-math verify '...' && ... therefore never reads a syntax error as a disproof.

A ready-to-use agent skill is in skills/axiom-math/SKILL.md.

HTTP Transport

# Start HTTP server (default: http://127.0.0.1:3000)
npm run start:http

# Development HTTP
npm run dev:http

The HTTP transport is stateless: every POST /mcp is handled independently, no Mcp-Session-Id is issued, and no session state is kept between requests. This server sends no server-initiated notifications, so nothing is lost — and it scales horizontally with no shared state.

| Method | Path | Behaviour | | ------ | --------- | ------------------------------------------------------ | | POST | /mcp | Handles a JSON-RPC message | | GET | /mcp | 405 — no SSE stream is offered | | DELETE | /mcp | 405 — there are no sessions to terminate | | GET | /health | 200 when ready, 503 when the CAS engine is not |

Security: there is no authentication and no rate limiting. The default bind address is 127.0.0.1, but docker/docker-compose.yml sets MCP_HOST=0.0.0.0. If you expose the port, put it behind a reverse proxy that authenticates and rate-limits — docker/reverse-proxy/ is a working, tested one (nginx + basic auth + per-client concurrency cap, with the app publishing no port of its own). SECURITY.md documents the full posture — what is protected, what is not, and how to report a vulnerability.

POST /mcp also validates the Host header against an

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars3
CategoryAI
Updated17d ago
Forks0

Languages

TypeScript

Trust signals

92/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 low