Browse and discover Model Context Protocol compatible servers
This repository offers a WebSocket-based Model Context Protocol (MCP) server and client implementation, including a local LLM chat bot demo, designed to improve upon existing MCP transport layers for efficient communication.
Provide high-speed real-time packet capture and network analysis with Rust-powered parsing and threat detection for efficient MCP server use.
MCP-based memory layer for Claude Cowork integrating TL;DV transcripts (Google Drive) with RAG-ready retrieval.
Store and retrieve persistent filesystem memory for LLMs and AI agents with structured, searchable context beyond token limits
The @fingertip/mcp repository provides a Model Context Protocol server for the Fingertip API, enabling AI assistants to manage Fingertip sites, retrieve site information, and create new sites. The @fingertip/mcp repository
Unify local AITool instances and remote MCP servers into a single, searchable execution surface with a .NET 10 library.
Provide an MCP server to enable reverse debugging with rr, improving control and insight during program execution analysis.
Scan MCP servers, AI agents, and LLM pipelines for security vulnerabilities and send results directly to your GitHub Security tab.
This repository provides an MCP server implementation for retrieving data from Volcengine TOS, exposing data through Resources like PDF documents. It offers tools for listing buckets/objects and retrieving objects, requiring
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📚 Index codebases and docs into Qdrant with Ollama embeddings, enabling AI assistants to search code via Model Context Protocol (MCP).
This repository provides an MCP server that generates TypeScript API clients from OpenAPI/Swagger specifications, enabling developers to easily interact with APIs using an axios-based client. This repository provides an MCP
Leviathan — это мощный MCP-сервер для удалённого управления Linux-системами через протокол MCP Model Context Protocol). Сервер автоматически определяет характеристики дистрибутива, доступные менеджеры пакетов, систему инициализации и графическое окружение, предоставляя единый интерфейс для выполнения типовых задач администрирования.
Manage and filter AI context and outputs locally using Rust-powered tools for precise control and improved response quality.