Open-source alternatives to McpProxy

VSCode Extension with an MCP server that exposes semantic tools like Find Usages and Rename to LLMs

Giving Claude ability to run code with E2B via MCP (Model Context Protocol)

Coding assistant MCP for Claude Desktop

An MCP server for interacting with Sentry via LLMs.

git-mcp is a Model Context Protocol server that transforms Git repositories and static sites into structured context providers for AI assistants. It functions as a documentation retrieval tool and repository indexer, exposing codebases and project files as standardized tools to reduce hallucinations in large language model responses. The project converts raw repository files, READMEs, and external URLs into formats optimized for token consumption. It enables AI agents to perform query-based code searches and retrieve specific sections of project documentation to maintain up-to-date technical

Securely run AI-generated code in stateful sandboxes that run forever.

A model context protocol server to work with JetBrains IDEs: IntelliJ, PyCharm, WebStorm, etc. Also, works with Android Studio

A Model Context Protocol (MCP) for Jupyter Notebook

MCP Server for RestCSV, Generated using MCPGen

Gymnasium-style RL framework for LLM agent training — MDP environments, three-layer process reward & SFT/DPO/GRPO policy optimization. CLI MCP ready.

mem0-mcp-server wraps the official Mem0 Memory API as a Model Context Protocol (MCP) server so any MCP-compatible client (Claude Desktop, Cursor, custom agents) can add, search, update, and delete long-term memories.

This project serves as an educational resource and implementation guide for the Model Context Protocol. It provides developers with the patterns and documentation necessary to standardize how large language models interact with external systems, local data sources, and various services. The repository focuses on facilitating the translation of technical documentation and educational materials into multiple languages. By utilizing an AI assistant integration framework, it enables the creation of localized learning resources that help developers master complex programming concepts regardless of

Semantic code searcher and codebase utility

Serena is a static site generator designed to transform markdown files into structured, navigable documentation websites. It functions as a documentation engine that processes source content into pre-rendered HTML pages, providing a clean and organized reading experience for technical manuals and knowledge bases. The platform distinguishes itself through a component-based layout framework that injects parsed content into reusable templates to maintain design consistency. It also features a built-in client-side search engine that constructs local databases, allowing users to retrieve informati

MCP server to run Python code in a sandbox.

Riza offers an isolated code interpreter for your LLM-generated code.

A MCP server for using Semgrep to scan code for security vulnerabilities.

Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run

Structural memory for AI coding agents. Bi-temporal graph, MCP-native, zero LLM calls. Cursor · Claude Code · Codex · Hermes · VS Code · Windsurf.

Java framework for building MCP servers with annotations. JSON Schema 2020-12 compliant, secure, lightweight.

Give AI agents X-ray vision into compiled Java code. Decompiles any class from Maven/Gradle dependencies via MCP.

A Model Context Protocol (MCP) server for interacting with Bugsnag. This server allows LLM tools like Cursor and Claude to investigate and resolve issues in Bugsnag.

A Model Context Protocol (MCP) server that provides line-oriented text file editing capabilities through a standardized API. Optimized for LLM tools with efficient partial file access to minimize token usage.

Context7 is an AI-powered documentation retrieval engine designed to provide developers and AI agents with real-time, context-aware access to technical documentation and code snippets. By integrating external library documentation as callable tools, the platform equips AI coding assistants with project-specific knowledge, helping to improve generation accuracy and reduce hallucinations during inference. The platform distinguishes itself through a robust security and governance framework that manages documentation as a centralized knowledge base. It employs a multi-source ingestion pipeline to

MCP server for document format conversion using pandoc.

DesktopCommanderMCP is a Model Context Protocol (MCP) server that gives AI agents direct access to local files, shell commands, and system processes through natural language instructions. It acts as a unified bridge between conversational commands and desktop operations, enabling an AI to translate plain English into file management, code editing, system command execution, data analysis, and software scaffolding tasks without needing its own API. The server exposes these capabilities as structured tools via the MCP protocol, so any compatible agent can interact with the local environment in a