MCP2Lambda is an MCP server that allows AWS Lambda functions to be used as tools for large language models (LLMs) without modifying the code. It builds a bridge between AI models and Lambda functions through the Model Context Protocol (MCP), enabling models to access private resources and perform custom operations.

The Logfire MCP server is a model context protocol service based on OpenTelemetry, which provides the ability for LLM to access application telemetry data and supports exception tracing and custom SQL queries.

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.

The Storybook MCP Server is a tool based on the model context protocol that provides functions for interacting with Storybook documentation and component information, including getting the component list, attribute details, and extracting specific information through custom JavaScript tools.

ai-create-mcp is a Go-based tool for converting OpenAPI specification files into Model Context Protocol (MCP) programs, supporting custom project settings and integration options.

This project is a proof-of-concept (POC) that demonstrates how to implement the Model Context Protocol (MCP) through a custom host for testing agentic systems. Core features include OpenAI-compatible API, Google Gemini integration, streaming response support, and tool invocation capabilities.

The Saleor MCP Server is a Model Context Protocol service designed for the Saleor e-commerce platform, allowing AI assistants to read product, customer, and order data through an HTTP connection and providing read-only API integration functions.

A template project for building a custom Model Context Protocol (MCP) server, providing the basic structure and tool implementation, and supporting integration with Cursor and Claude Desktop.

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.

This project provides a comprehensive guide for implementing a Model Context Protocol (MCP) server for Cursor AI, including basic concepts, implementation steps, code examples, and integration requirements, aiming to enhance the AI's capabilities through custom tools.

This is a Spring Boot Starter for automatically integrating MCP (Model Control Protocol) services, supporting non - intrusive enhancement and custom tool parsing, and simplifying AI interface development.

The CrewAI MCP Adapter is a Python library that extends the CrewAI adapter ecosystem by integrating the Model Context Protocol (MCP), providing comprehensive support for custom agent and tool development.

A customized version of NextChat that creates and deploys MCP servers through chat interactions, integrates LLM models from OpenRouter, and provides functions such as tool extraction, one-click deployment, and AI system integration guides.

The MCP Game Helper is a custom model context protocol server that provides AI - assisted tools for game developers, focusing on tasks such as combat balance, skill analysis, level rhythm, and simulation.

An implementation of a k6 load testing server based on the Model Context Protocol framework, supporting custom test durations and the number of virtual users, providing simple APIs and real-time test outputs.

Claude Team is a multi - agent MCP server that enables intelligent task distribution, preset workflow templates, and a custom expert system by configuring multiple AI models (such as GPT, Claude, Gemini) to work together, for automated collaboration on complex development tasks.

The Gemini MCP Server is a middleware designed for the Claude desktop application, enabling image generation through Google's Gemini AI model. This project provides a convenient installation and configuration wizard, supports Docker containerized deployment, and allows users to customize generation parameters.

A production-ready MCP server template for hosting custom AI tools and prompt templates, supporting remote deployment and local operation, helping developers quickly build AI model interaction tools.

A chat platform integrating LangChain, a custom MCP server, and Google Gemini AI model, providing enhanced conversation functions.

Infobip MCP servers allow AI agents to interact with the Infobip platform via the Model Context Protocol, support sending messages via multiple channels such as SMS, WhatsApp, and Viber, manage customer data and user accounts, and provide production-level communication services

The Ideogram MCP Server is an image generation service based on the Ideogram API, providing a variety of customizable image generation parameters, including ratio, model, style, etc.

SearXNG MCP is a model context protocol server based on the SearXNG privacy-protecting metasearch engine, providing web search functionality for AI assistants. It supports zero-configuration use of public instances or connection to private instances, with features such as customizable search parameters, multi-search engine support, and privacy-first.

This project demonstrates an example implementation of the Model Context Protocol (MCP), which is a standardized protocol for enhancing the capabilities of AI assistants and extending their functionality through custom tools and data sources. The project includes multiple MCP server examples, such as task managers, file explorers, and weather services, and provides guidelines on how to set up and use these servers.

Unity - MCP is a bridge tool that connects large language models (LLMs) and the Unity Editor. By exposing Unity Editor functions to AI clients, it enables an AI - driven automated development process. It supports custom tool extensions and currently provides core functions such as game object management, scene operations, and asset handling. It is mainly suitable for the Unity Editor environment.

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers, covering multiple fields such as browser automation, art and culture, cloud platforms, command - line tools, communication, customer data platforms, databases, developer tools, file systems, finance and fintech, games, knowledge and memory, location services, marketing, monitoring, search, security, travel and transportation, version control, and other tools and integrations.

An advanced reasoning and reflection tool based on the Gemini API, supporting multi - model integration and custom configuration

MCP Server Notifier is a lightweight notification service integrated with the Model Context Protocol (MCP), which can send Webhook notifications when an AI agent completes a task. It supports multiple Webhook providers (e.g., Discord, Slack, Teams, etc.), provides features such as image support, multi - project management, and custom messages, and is easy to integrate with AI tools (e.g., Cursor).

A high-performance MCP server based on Rust that encapsulates the Factory.ai Droid CLI tool, providing AI-assisted programming capabilities for MCP clients such as Claude Code. It supports full Droid parameter mapping, session management, custom models, and fine-grained permission control.

A Node.js-based custom prompt server for the Claude AI model, supporting modular classification management and chained prompt execution.

The GitScrum MCP Server is an official Model Context Protocol (MCP) service that transforms AI assistants (such as Claude, Cursor) into fully - featured project managers, providing in - depth context and operational access to GitScrum workspaces (tasks, sprints, time tracking, customer relationship management, analysis, etc.).

iRacing MCP is a Python project that integrates iRacing data through the Model Context Protocol, providing tools for obtaining user data and building custom applications.

This project realizes the communication between the DingTalk AI assistant and the locally privately deployed MCP service, supports multi - model configuration and local operation, and provides the ability to develop custom functions.

The Mandoline MCP Server is an AI assistant evaluation framework that provides tools for creating custom evaluation metrics, batch scoring, and performance analysis for AI assistants such as Claude and Cursor through the Model Context Protocol, helping AI continuously improve its own performance.

The JetBrains MCP Server plugin enables seamless integration of large language models with JetBrains IDEs, providing server-side processing and custom tool extension points.

A proof - of - concept project for a server implementing the Model Context Protocol (MCP), providing custom tools and resources to enhance the capabilities of AI assistants, including document search, web page crawling, and Google Search API integration.

Crawl4AI is an intelligent web crawler server based on the MCP architecture. It combines the Claude AI model to provide website content analysis and processing functions, supports customizable crawling depth and AI processing tasks, and is suitable for various scenarios such as research, content creation, and data analysis.

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers that cover a variety of tools and integrations, including browser automation, art and culture, cloud platforms, command - line, communication, customer data platforms, databases, developer tools, file systems, fintech, knowledge and memory, location services, monitoring, search, security, travel and transportation, version control, etc. MCP is an open protocol that enables AI models to securely interact with local and remote resources through standardized servers.

An MCP server based on the Google Custom Search API, providing a standardized web search interface for large language models

The Freshdesk MCP Server is an AI support tool that integrates with Freshdesk, enabling AI models to perform various customer service operations through the Freshdesk module.

An MCP protocol server based on the Google Custom Search API that provides a standardized web search interface for language models, supporting environment variable configuration and type-safe implementation.