MCP Go is a server-side framework for the Model Context Protocol (MCP) implemented in Go, used to connect LLM applications with external data sources and tools. It provides core functions such as resource management, tool invocation, and prompt templates, and supports session management and middleware extension.

MCP-Scan is a security scanning tool for MCP servers, used to detect common security vulnerabilities such as prompt injection, tool poisoning, and cross-domain escalation.

The MCP-Framework is a TypeScript-based framework for elegantly building Model Context Protocol (MCP) servers. It provides an out-of-the-box architecture, supports automatic directory discovery of tools, resources, and prompts, and has multiple transmission methods and type-safe features.

FastMCP is a TypeScript-based framework for building MCP servers that support client sessions. It provides simple definitions for tools, resources, and prompts, supports functions such as authentication, session management, returning image and audio content, logging, error handling, SSE communication, etc., and includes CLI tools for testing and debugging.

Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.

Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.

The DevOps AI Toolkit is an AI-based platform engineering and DevOps automation tool that provides functions such as resource deployment recommendations, problem repair, project governance, and a shared prompt library for teams through intelligent Kubernetes operations and conversational workflows, enabling complex cloud-native operations to be achieved through natural language interaction.

A service based on the Model Context Protocol (MCP) that supports the specification-driven development process, guiding developers through a systematic development process from requirement generation, design documents to code implementation via structured prompts.

LiteMCP is a TypeScript framework for elegantly building MCP (Model Context Protocol) servers. It provides the definition of tools, resources, and prompts, supports full - TypeScript development, has built - in logging, error handling, and CLI debugging tools, as well as SSE transmission support.

Pipelock is an open-source AI agent firewall that provides security protection with zero runtime dependencies through a single binary file. It adopts an architecture with separated capabilities and deploys a nine-layer scanning pipeline between the agent and the Internet to prevent secret leakage, prompt injection, and malicious tool calls. It supports multiple proxy modes (Fetch proxy, forward proxy, WebSocket proxy) and MCP proxy, and provides functions such as an emergency stop switch, audit logs, and SIEM integration.

A NestJS module for easily exposing AI tools, resources, and prompts via the Model Context Protocol (MCP), supporting multiple transport types and automatic discovery and registration functions.

The Dify MCP client plugin, as an agent strategy plugin, allows ReAct agent nodes to connect to the MCP server, converting the list of tools, resources, and prompts into Dify tools for LLM to call.

MetaMCP is a proxy server for integrating and managing multiple MCP servers, providing unified tool/prompt/resource configuration and request routing functions.

The MCP Anthropic Server is a server - side project that provides tools for interacting with Anthropic's experimental prompt engineering API.

An image processing server based on the MCP protocol that enables professional - level image editing functions through natural language instructions, including generation, modification, background removal, and hosting services.

A Model Context Protocol (MCP) server template project based on TypeScript, providing a structured, maintainable and extensible framework, including implementation examples of tools, resources and prompts, supporting configuration management, logging, error handling and containerized deployment.

An MCP diagnostic tool developed specifically for Trae IDE, which can obtain real-time error, warning, and prompt information in the project, helping the AI Agent provide accurate code analysis and repair suggestions.

An MCP server based on TypeScript, designed specifically for Drupal, providing resource, tool, and prompt functions, and supporting integration with Claude Desktop.

oatpp-mcp is an implementation of Anthropic's Model Context Protocol (MCP) based on the Oat++ framework, supporting auto-generated API tools, STDIO and HTTP SSE transmission methods, as well as server functions such as prompts, resources, and tools.

mcp-chat is an open-source and general-purpose MCP client tool for testing and evaluating MCP servers and proxies. It supports command-line interaction and web mode, can connect to various MCP servers (JS/Python/Docker), and provides functions such as chat history recording, model selection, and system prompt customization to help developers debug MCP services.

MCP is an open-source protocol for standardizing LLM interactions, providing a unified framework for connecting data sources, obtaining context, using tools, and executing standard prompts. Project examples demonstrate how to build MCP servers and clients to implement knowledge base chatbot functionality.

The Claude MCP server for GB Studio is used to create and modify GameBoy game projects through natural language prompts, supporting visual programming and AI-assisted development in educational scenarios.

A TypeScript-based MCP server that uses OpenAI's DALL-E 3 model to generate images based on text prompts.

WebMCP is a project that allows websites to support client-side LLMs (Large Language Models). It enables the sharing of tools, resources, and prompts between websites and LLMs through a local WebSocket server without the need for API keys and supports multiple models.

An enhanced MCP server that supports intelligent retrieval, combination, and management of prompts from GitHub repositories, providing advanced search, real-time synchronization, and usage analysis functions.

A text editing system integrated with Claude Desktop, which realizes text selection, editing, and automatic replacement functions at the macOS system level through the MCP protocol, supporting custom prompts and desktop notifications.

The Meta Prompt MCP project simulates a multi - agent collaboration system through a single language model, realizing task decomposition and expert consultation functions, and simplifying the process of solving complex problems.

Prompt Decorators is a framework for standardizing large - language - model prompt enhancement and transformation. It provides specification definitions and Python implementations, includes over 140 pre - set decorators, and supports MCP protocol integration.

This project is an MCP server for managing memory text files, helping AI models like Claude maintain context between conversations. It provides functions to add, search, delete, and list memories, supporting exact matching operations based on substrings. It is designed to store memories in simple text files, similar to ChatGPT's memory mechanism, and triggers memory storage through prompts and training.

This project is a CSS teaching MCP server built on Node.js and TypeScript, providing personalized CSS feature update services, including resource management, tool invocation, and prompt guidance functions.

The ChatData MCP Server is a framework based on the Model Control Protocol, providing a toolset, prompt system, and resource management to enhance the capabilities of large language models.

GistPad MCP is a Node.js-based server for managing personal knowledge, daily notes, and reusable prompts via GitHub Gists. It works with the VS Code extension and the GistPad.dev website, supporting access to and editing of Gists from any MCP-compatible AI product.

An AI agent server based on the Model Context Protocol, providing system prompt and tool management functions

An MCP server based on Claude AI for optimizing programming prompts and enhancing the usage experience in AI IDEs such as Cursor.

rs_filesystem is a simple file system toolset that can be used in the Claude desktop or other MCP clients, providing functions for displaying resources, prompts, and tools, and communicating through the MCP protocol.

Achieve AI - driven design automation in Figma through natural language prompts

A PHP-based tool for quickly building MCP servers, supporting the creation of tools, exposure of resources, and definition of prompts, simplifying LLM context management.

Deep-Co is a cross-platform chat client developed based on Compose Multiplatform. It supports multiple LLM API providers, including OpenRouter, Anthropic, Grok, OpenAI, etc., and is compatible with OpenAI API and local models. It has functions such as chat record management, prompt management, role adaptation, TTS, etc., and supports multiple languages and theme customization.

The Enkrypt AI MCP Server is a tool integrating red team testing, prompt auditing, and AI security analysis, supporting integration with MCP - compatible clients.

An MCP server for image generation and editing based on the OpenAI gpt-image-1 model, supporting the creation and modification of images through text prompts, providing convenient integration methods and rich configuration options.