"Using a cursor to code or implement functionality" matching MCP servers:

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

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

Enables cost-effective repository analysis, code search, file editing, and task planning by wrapping the cursor-agent CLI through focused tools. Reduces token usage by offloading heavy thinking tasks from Claude to specialized operations with configurable output formats.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables AI agents to run untrusted, model-generated Python code in a locked-down throwaway Docker container with enforced isolation and resource limits. Supports starting, checking, and stopping asynchronous runs while returning structured status reports without exposing the host, network, or Docker controls.

An MCP server that implements Claude Code-like functionality, allowing the AI to analyze codebases, modify files, execute commands, and manage projects through direct file system interactions.

MCP server for E2B code sandbox, enabling creation, management, and execution of code in secure sandboxes using Python and shell commands.

An MCP server that provides code review functionality using OpenAI, Google, and Anthropic models, serving as a "second opinion" tool that works with any MCP client.

A MCP server for managing and storing code snippets in various programming languages, allowing users to create, list, and delete snippets via a standardized interface.

A Model Context Protocol server that helps large language models process code repositories by providing file tree generation, code merging, and code analysis capabilities.

An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically

Provides tools for AI-driven development workflows including file system operations, code analysis, code execution, web fetching, and search.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

Execute Python, JavaScript, or SQL code in a sandboxed environment and retrieve stdout, execution time, and errors with pay-per-call via x402 (USDC on Base L2).

Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.

Enables Codex to offload expensive code reading, editing, and checking to a worker agent via Claude Code, supporting async jobs and long-running tasks.

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.