"Information about the programming language Rust" matching MCP servers:

Provides coding tutoring by running checks for common programming tasks (palindrome, prime, Fibonacci, GCD, etc.) and explaining the results in plain language.

A simple MCP server that integrates Rust functions via WebAssembly, enabling operations like factorial computation through Claude Desktop.

Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.

Enables AI agents to directly manipulate Jupyter Notebook cells and structure through a secure, well-defined API, overcoming Cursor's AI agent mode limitations.

Enables AI agents to generate, compile, and fix Rust projects from natural language descriptions using LLMs and the Rust compiler.

Enables local, Docker-isolated code execution across six programming languages including Python, Rust, and TypeScript. It features pre-warmed container pooling, persistent sessions, and built-in support for machine learning libraries.

Enables mathematical computation via Wolfram Language/Mathematica integration, supporting calculations, equation solving, calculus, matrix operations, and symbolic mathematics.

Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.

Give your AI app any GitHub link and the job you want done. UGT gets the project running on your computer and hands you the result.

An MCP server that lets AI models run code in 31 languages, evaluate symbolic math and logic problems, and measure complexity—exposed as 48 tools for execution, session management, translation, optimization, and more.

Enables AI assistants to run code in 24 programming languages on HackerEarth's sandboxed servers and read the printed output or errors, without installing local toolchains. It also lists supported languages with exact identifiers for use when submitting code.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Control the Unity Editor from any MCP host. One package install, one click, and your AI assistant can see your scene, create objects, and talk to the console. Patina is a Rust MCP server paired with a C# Unity bridge. It connects your favorite AI coding tool directly to the Unity Editor over a local TCP channel, with zero manual config.

Analyzes codebases to generate dependency graphs and architectural insights across multiple programming languages, helping developers understand code structure and validate against architectural rules.

Enables AI clients to create, edit, run, and inspect ScratchJr Desktop projects using natural language, including characters, backgrounds, text, sounds, and programming blocks.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

Connects 3D Slicer with AI assistants through the Model Context Protocol, enabling medical image processing and scene manipulation using natural language.

Enables dynamic creation and execution of custom tools/functions in multiple programming languages at runtime, exposing them to MCP clients like Claude.

Connects AI assistants to the Repovive competitive-programming platform, enabling them to browse problems and contests, judge and submit code for real verdicts, track ratings, communicate with users, and author verified problems and rounds.

Enables compiling Lean 4 proof snippets on the local machine against a Mathlib project and returns structured compiler feedback — status, one-line hints, and the compiler's real error, warning, and information messages — so a model can iterate on proofs instead of guessing. Compilation is serialized, timeouts kill stuck tactics, and rejected code is reported as a normal result rather than a tool failure.

The toolchain of Renyi, a programming language for AI agents: check, format, run and test programs, and read the project map with every function's effects, semantic diffs and chunks for retrieval. One binary, renyi mcp.

Enables agents to create, share, and collaboratively edit temporary encrypted Rust playgrounds with complete capability links, offering revision-safe file reads and edits plus handoff to other agents or people. It also supports discovering browser or device runtime clients and requesting human-approved local Run and Debug operations.

Exposes local NVIDIA GPU (CUDA) and Rust-to-WASM toolchain as MCP tools for sovereign local compute.

An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.

A Pyodide server for executing Python code by Large Language Models (LLMs) via the Model Context Protocol (MCP).

Enables debugging of Python, JavaScript/TypeScript, Go, and Rust code using real debuggers with breakpoints, stepping, variable inspection, and stack trace navigation through the Debug Adapter Protocol.

A comprehensive learning project demonstrating MCP server implementation with tools for calculator operations, file management, and system information retrieval, including Google ADK integration patterns and best practices.

Transforms unstructured natural language operational problems into rigorously formulated, validated, and solved Mixed-Integer Linear Programming (MILP) models via an autonomous multi-agent graph, bringing closed-loop Operations Research capabilities to LLM assistants and MCP clients.

Extracts minimal, relevant code context from multiple programming languages while analyzing diffs and optimizing imports to reduce token usage for AI assistants. Supports TypeScript/JavaScript, Python, Go, and Rust with token-aware caching.