"How to check differences between files" matching MCP servers:

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.

A Model Context Protocol (MCP) server that converts LaTeX mathematical expressions to MathML format.

Exposes the Grok Build CLI as MCP tools for Claude Code and other clients, enabling headless AI agents to perform tasks like code reviews, web research, and file operations with configurable permission levels.

Enables AI assistants to write and execute C# code directly inside Autodesk Civil 3D, providing full API access through code generation and execution.

Bridges Claude Desktop with Claude Code CLI to delegate complex coding tasks like creating React apps, building APIs, and debugging scripts while maintaining interaction through the Desktop interface.

Converts Figma designs to React Native components, allowing users to extract components from Figma designs and generate corresponding React Native components with proper typing and styling.

Integrates ElevenLabs Text-to-Speech capabilities with Cursor through the Model Context Protocol, allowing users to convert text to speech with selectable voices within the Cursor editor.

Provides MCP tools to create, run commands in, checkpoint, and delete durable cloud environments, giving coding agents persistent state between calls.

A Python code execution sandbox based on IPython and Docker. Stateful code execution, file transfer between host and container, configurable network access.

MCP bridge between an AI assistant and the Godot editor, enabling control via 6 tools (call methods, run GDScript, screenshots, etc.) over WebSocket.

Enables AI coding agents and IDEs to lint, compile, syntax-check, and simulate Verilog/SystemVerilog designs through structured, token-efficient MCP tools with isolated containerized toolchains.

An MCP server for LaTeX that enables AI assistants to check documents for errors, parse compiler logs, and compile LaTeX files, helping them fix documents instead of guessing.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

A demonstration server that reveals security risks by accessing sensitive environment variables, illustrating how MCP tools can potentially leak user data without explicit consent.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

MCP server that exposes Ansible modules to AI agents with a search-schema-check-execute workflow, enabling safe ad-hoc runs via check mode by default. It provides tools to search modules, fetch schemas, run modules, and list collections.

A professional implementation of a Model Context Protocol server that enables integration between DaVinci Resolve video editing software and AI assistants like Claude Desktop or Cursor.

MCP Server for the Peacock extension for VS Code (https://peacockcode.dev), coloring your world, one Code editor at a time. The main goal of the project is to show how an MCP server can be used to interact with APIs.