20 Awesome MCP Servers List I Have Collected (You Should Try Too)
In the rapidly evolving landscape of AI assistance, Model Context Protocol (MCP) servers have emerged as game-changers. These powerful tools bridge the gap between AI models like Claude and external resources—from file systems to web services. By leveraging MCP servers, you can dramatically enhance your AI's capabilities, automating tasks and accessing data that would otherwise be beyond reach.
MCP servers function as secure intermediaries that allow AI models to interact with local and remote resources. Whether you need to manage GitHub repositories, search the web, analyze databases, or organize files, these servers make it possible with minimal setup. The result? A more productive workflow where your AI assistant becomes truly helpful in your daily tasks.
Whether you're a developer looking to streamline coding workflows, a content creator managing multiple platforms, or simply someone who wants to be more productive, there's likely an MCP server (or several) that can help you achieve your goals. Start with the ones most relevant to your needs, and remember to explore himcp.ai for even more options as the ecosystem continues to grow.
File and Data Management
1. File System MCP Server
Description: This essential server grants AI assistants access to your local file system, enabling operations like reading, writing, creating, and deleting files and directories. With configurable permissions, you can control exactly what the AI can access.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem
2. Google Drive MCP Server
Description: Access your Google Drive contents directly through AI interactions. Search for files, read documents, upload new content, and organize your cloud storage without ever leaving your conversation.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/google-drive
3. Memory MCP Server
Description: A specialized server that provides persistent memory capabilities for AI interactions, allowing the model to store and retrieve information across sessions without forgetting important context.
Link: https://github.com/anthropics/anthropic-cookbook/tree/main/mcp/memory
Developer Tools
4. GitHub MCP Server
Description: This powerful server enables AI to interact with GitHub repositories, view code, create issues, manage pull requests, and more. Perfect for developers looking to streamline their workflow with AI assistance.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/github
5. Git Ingest MCP Server
Description: Created by adhikasp, this Python-based server lets AI models read and analyze entire GitHub repositories. It's invaluable for understanding codebases and providing context-aware assistance.
Link: https://github.com/adhikasp/mcp-git-ingest
6. Godoc MCP Server
Description: A token-efficient Go documentation server that provides AI assistants with smart access to package docs and types without reading entire source files. Essential for Go developers.
Link: https://github.com/mrjoshuak/godoc-mcp
7. Quarkus JDBC MCP Server
Description: This server leverages the Java ecosystem to connect AI models with any JDBC-compatible database. Its compact implementation and wide compatibility make it a powerful tool for database interactions.
Link: https://github.com/quarkiverse/quarkus-mcp-servers
Web and Search
8. Fetch MCP Server
Description: A simple yet powerful server that allows AI models to retrieve content from URLs. It handles fetching web pages, API responses, and various data formats, making internet data accessible.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/fetch
9. Brave Search MCP Server
Description: Integration with Brave's privacy-focused search engine, allowing AI to perform web searches while respecting user privacy. Get up-to-date information without compromising on data protection.
Link: https://github.com/brave/brave-search-mcp
10. Exa MCP Server
Description: Leverages Exa's AI-powered search API to provide highly relevant search results for specific queries. Particularly useful for research and technical information gathering.
Link: https://github.com/exa-ai/mcp-server
11. Kagi MCP Server
Description: Connect to Kagi's premium search service, known for its high-quality results and absence of ads. This server offers AI models access to Kagi's unique search capabilities.
Link: https://github.com/kagi-search/mcp-server
12. Vector Search MCP Server
Description: A specialized server that enables semantic searching through vector embeddings. Perfect for finding related documents, clustering data, and powering machine learning workflows.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/vector-search
Communication and Collaboration
13. Slack MCP Server
Description: Integrate your AI assistant with Slack workspaces to send messages, retrieve channel history, and automate routine communications. Ideal for managing team notifications and daily standups.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/slack
14. Contentful MCP
Description: Created by ivo-toby, this server allows AI to update, create, delete content, content-models, and assets in your Contentful Space. A must-have for content managers using Contentful.
Link: https://github.com/ivo-toby/contentful-mcp
15. Apify Actors MCP Server
Description: Access over 3,000 pre-built cloud tools (Actors) for extracting data from websites, e-commerce platforms, social media, search engines, maps, and more. A powerful data collection toolkit.
Link: https://github.com/apify/actors-mcp-server
AI Integration
16. OpenAI MCP Server
Description: This server by mzxrai enables Claude to communicate with OpenAI's most advanced models, creating a powerful synergy between different AI systems. Perfect for specialized tasks where multiple AI perspectives are valuable.
Link: https://github.com/mzxrai/mcp-openai
Cloud and Infrastructure
17. Cloudflare MCP Server
Description: Harness Cloudflare's edge computing capabilities for deploying and managing web applications. This server assists with security, performance optimization, and global content delivery.
Link: https://github.com/cloudflare/workers-mcp-server
18. Raygun MCP Server
Description: Connect to Raygun's application monitoring platform to track errors and performance issues in real-time. Essential for maintaining reliable services and quickly identifying problems.
Link: https://github.com/MindscapeHQ/raygun-mcp-server
Advanced Utilities
19. PostgreSQL MCP Server
Description: A specialized server for interacting with PostgreSQL databases, offering secure, read-only access for querying data. Includes schema inspection features to ensure safe database interactions.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/postgresql
20. Puppeteer MCP Server
Description: Leverage Puppeteer's browser automation capabilities for web scraping, testing, and complex web interactions. This server enables AI to navigate websites and extract information from dynamic web pages.
Link: https://github.com/modelcontextprotocol/servers/tree/main/src/puppeteer
Why MCP Servers Matter
The power of MCP servers lies in their flexibility and extensibility. Unlike traditional plugins that require manual installation or code updates, MCP servers can be added to your environment dynamically, allowing your AI client to pick up new capabilities on the fly. This means your AI toolkit can evolve as new servers become available, without requiring extensive reconfiguration.
Moreover, the MCP protocol is designed to be adaptable, not limited to a fixed set of operations. Developers can define new types of tools or resource formats as needed, and as long as they adhere to the protocol structure, any client can utilize them. This open approach fosters innovation and ensures that your AI assistant can grow alongside your needs.
Getting Started
Most MCP servers follow a similar setup pattern: installation via npm or another package manager, configuration with appropriate API keys or credentials, and testing with simple commands. Documentation for each server typically provides step-by-step instructions tailored to that specific tool.
For Claude users, many of these servers work with Claude Desktop, requiring simple configuration updates in your claude_desktop_config.json file. After configuration, you can immediately start using new capabilities by asking Claude to perform tasks using the newly connected resources.
Conclusion
The Model Context Protocol represents a significant advancement in making AI assistants truly useful for everyday tasks. By connecting AI models to external resources, MCP servers expand what's possible in your conversations, turning theoretical capabilities into practical tools.
Looking for More MCP Servers?
This article covers 20 of the best MCP servers available today, but the ecosystem is growing rapidly. For an even more comprehensive collection of MCP servers beyond what we cover here, check out himcp.ai, which maintains an up-to-date directory of available servers for all your needs.