"Manim - Python Library for Animations and Math Visualization" matching MCP servers:

Enables compilation and serving of Manim animations through natural language. Supports compiling Manim Python code into videos and downloading the generated animations with secure authentication.

Enables LLM agents to generate labeled contact sheets of Manim animations, scaffold storyboards from renders, and validate rendered steps against expected intents via MCP tools.

A server-based tool that enables the generation of mathematical animations from natural language prompts by leveraging Manim.

A comprehensive math utility server implementing the Model Context Protocol (MCP) for reverse engineering and general-purpose arithmetic, bitwise, conversion, and encoding tasks via streamable HTTP.

Provides exact arithmetic and verification tools using SymPy and fractions to solve math competition problems precisely. It enables users to perform rigorous calculations and export notebook-ready Python code for further analysis.

Implements a math agent using Model Control Protocol that performs mathematical calculations and visually presents results in Keynote, enabling drawing shapes and adding text to slides.

A secure MCP server for evaluating mathematical expressions with grammar validation, function whitelisting, and sandboxed execution. It provides tools for expression evaluation, variable management, and resources for grammar and function documentation.

Enables safe math expression evaluation, unit conversion, statistical analysis, number formatting, and percentage calculations for AI agents via MCP.

A Model Context Protocol server that provides basic mathematical and statistical functions to LLMs, enabling them to perform accurate numerical calculations through a simple API.

Provides LLMs with deterministic math tools for sandboxed expression evaluation, descriptive statistics, primality testing, prime factorization, GCD/LCM, quadratic solving, and base conversion. Every operation runs real code rather than relying on the model's arithmetic, with expression parsing restricted to a whitelist of operators, constants, and functions.

Enables coding agents to establish exact-release library identity, search provenance-tracked API, docs, example, source, and release evidence, compare releases, and test proposed invocations in isolated capsules for Rust and Python dependency environments.

Provides secure mathematical computation capabilities including expression evaluation, symbolic math (derivatives, simplification), matrix operations, statistics, and unit conversion, with multi-tier acceleration through WebAssembly and WebWorkers for high-performance calculations.

Enables automatically generating standalone MCP servers from any Python library, exposing its functions as deterministic callable tools.

Provides 21 mathematical tools across 6 domains including basic calculations, array operations, statistics, financial mathematics, linear algebra, and calculus. Supports batch execution for complex multi-step workflows with intelligent dependency resolution.

Enables basic arithmetic operations (addition, subtraction, multiplication, division) with 64-bit precision and matrix multiplication capabilities. Provides mathematical computation tools for AI assistants through the Model Context Protocol.

MCP server exposing pure mathematical operations (sum, subtraction, multiplication, division) as tools, with a clean layered architecture and optional OpenAI Agents SDK integration.

A Model Context Protocol server that exposes 8 mathematical tools (arithmetic, algebra, calculus, matrix operations, statistics, probability, unit conversions) to any MCP-compatible AI agent, enabling mathematical computations without code.

This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.

A Mathematical Computation Protocol server providing 286 mathematical functions across multiple domains with flexible transport options (STDIO/HTTP) and streaming capabilities.

Architectural Gatekeeper for AI coding. Prevents "tunnel vision" bugs by forcing the AI to verify dependencies (via AST parsing) before editing files. Supports JavaScript & TypeScript. Blocks unsafe edits until the AI proves it understands the impact