The AWS MCP Servers are a set of dedicated servers based on the Model Context Protocol, offering various AWS-related functions, including document retrieval, knowledge base query, CDK best practices, cost analysis, image generation, etc., aiming to enhance the integration of AI applications with AWS services through a standardized protocol.

This is a continuously updated curated list of MCP servers, covering multiple categories such as browser control, art and culture, cloud platforms, command - line, communication, customer data platforms, databases, developer tools, data science tools, file systems, finance and fintech, games, knowledge and memory, location services, marketing, monitoring, search, and utilities. Each project comes with a GitHub link and the number of stars, making it easy for users to quickly understand and use.

Awesome MCP Servers is a comprehensive collection of Model Context Protocol (MCP) servers, covering 7,158 MCP servers divided into 33 categories, including AI integration, art and media, browser automation, cloud services, databases, developer tools, file systems, finance, gaming, hardware, healthcare, infrastructure, knowledge management, location maps, marketing, monitoring, multimedia processing, operating systems, project management, scientific research, security, social media, travel and transportation, utilities, and version control, etc.

Archon is an intelligent system for autonomously constructing and optimizing AI agents. It demonstrates key principles of modern AI through iterative development, including agent reasoning, domain knowledge integration, and scalable architecture. The current version V4 provides a comprehensive Streamlit interface, supports Docker deployment, and integrates with MCP services for seamless docking of the AI IDE.

This project is a list of MCP servers, covering multiple fields such as browser automation, tool integration, system automation, AI services, search, commands, workflow automation, social media, communication, customer data platforms, databases, knowledge storage, development tools, file systems, cloud storage, finance, location services, monitoring, research data, security, travel, data visualization, notes, marketing, identity, etc.

The Shared Knowledge MCP Server is a middleware that provides unified knowledge base services for multiple AI assistants, enabling efficient information retrieval and sharing through RAG technology.

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.

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.

Bocha is a search engine designed specifically for AI, providing high-quality world knowledge retrieval services.

This project is a list of MCP servers implemented in Go, including multiple services for natural language processing and database interaction, such as text-to-SQL and knowledge base retrieval. It supports multiple platforms, is open-source, and free of charge.

The Model Context Protocol (MCP) is a standardized protocol introduced by Anthropic for the interaction between large language models (LLMs) and external tools and functions, as well as for injecting context into LLMs. It enables models to request real-time information, perform operations in external systems, access professional knowledge bases, and interact with APIs and services. The MCP is similar to a USB hub, serving as a standard interface that reduces the risk of API changes because each MCP server is maintained by its own company, and users only need to integrate it. The MCP server provides three functions: tools, resources, and prompts.

This is a comprehensive collection of Model Context Protocol (MCP) servers, covering multiple categories such as AI services, art and culture, browser automation, cloud platforms, cloud storage, command lines, communication, customer data platforms, data science tools, databases, developer tools, file systems, finance, games, knowledge and memory, location services, marketing, monitoring, notes, other tools and integrations, research and data, search, security, social media, system automation, travel and transportation, version control, and workflow automation.

The Valyu MCP Server is a model context protocol server that provides knowledge retrieval and feedback API services.

This project uses Docker Compose to set up multiple Model Context Protocol (MCP) services, including Git operations, file systems, PostgreSQL databases, knowledge graph storage, and visual debugging tools, providing a complete local development environment deployment solution.

The GPTers Search MCP Server is an MCP server that provides knowledge search services for the GPTers AI learning community, supporting the retrieval of community content through the MCP protocol to clients.