An official Microsoft document-conversion tool that turns Word, PDF, Excel and PPT into Markdown in one click, so AI can read your documents directly.
MCP Encyclopedia
Model Context Protocol — a USB-C connector that lets AI plug into everything. What it is, curated servers, and configuration guides.
What is MCP?
MCP (Model Context Protocol) is a standard open-sourced by Anthropic in November 2024 that solves a real problem: AI applications (desktop clients, IDEs and the like) need to connect to external tools and data sources (databases, GitHub, browsers…). Previously every tool had to be custom-built for each app; MCP turns this into a unified “USB-C interface”.
There are three roles: your AI application is the host, the MCP program providing a capability is the server, and they connect through the MCP protocol. Install a GitHub MCP server and your AI can manage repositories directly; install a browser MCP and your AI can operate web pages for you.
Today there are more than 15,000 MCP-related repositories on GitHub and nearly 10,000 officially registered servers — one of the most important pieces of infrastructure in the AI tool ecosystem.
Unified standard
Connect once, and any MCP-supporting AI can use it.
Extensible
Databases, search, automation, 3D… capabilities plug in and go.
Huge ecosystem
Close to 10,000 official plus community servers covering every scenario.
Open Settings → Developer → Edit Configuration (claude_desktop_config.json) and add the server config under the mcpServers field. Each server's specific parameters are in its project README — jump straight to them from this page.
Essential Guides
What is MCP? A Deep Dive into the Model Context Protocol
The open protocol that connects AI clients to tools and data — concepts, architecture, and how it works.
Read more → FAQMCP FAQ: 12 Common Questions Answered
What MCP is for, whether you need it, and how to pick servers — quick answers in one place.
Read more → WalkthroughCommon MCP Server Walkthroughs: GitHub, Browser, Documents
Hands-on with GitHub, Playwright browser automation, and MarkItDown document conversion.
Read more → SecurityMCP Security Guide: Permissions and Data Risks
What to check before installing a server — permissions, data access, and safe defaults.
Read more → TutorialMCP Configuration Guide: Installing Servers for Claude Desktop / Cursor
Where the config file lives, the JSON structure, and per-client setup steps.
Read more → ChoosingWhich MCP Servers Should Your AI Client Use?
A client selection guide: match popular servers to what you actually do.
Read more →Featured MCP Servers
Star counts as of the 2026-09-02 snapshotThe most authoritative collection of MCP servers on GitHub: hundreds of servers organized by use case. The first place to look when hunting for MCP tools.
Let your AI agent see the entire internet: read and search content from Twitter, Reddit, YouTube, GitHub and more. An essential tool for information-seeking agents.
A context-optimization layer for LLM applications that automatically manages the context window — dramatically improving agent performance in long conversations and large codebases.
Indexes an entire codebase into a persistent knowledge graph: supports 35 languages with millisecond queries, roughly 99% faster than grep. Long-term memory for coding AI agents.
An official Microsoft MCP server for browser automation: lets AI agents control a browser to click, fill forms, screenshot and scrape. The go-to for web automation.
The official GitHub MCP server: lets AI agents directly manage repositories, PRs and issues. A core component of developer automation workflows.
AIHawk, an automated job-application assistant: a browser-based AI agent that browses job listings, customizes your resume and applies for you. A job-hunting automation wonder.
Lets AI command Blender through natural language for 3D modeling, scene creation and editing. A flagship project for creating 3D assets with prompts.
The official MCP Python SDK: quickly build MCP servers and clients in Python. Officially maintained with thorough docs — the standard starting point for developers.
A lightweight cross-platform database client at just 20MB, with built-in MCP support that lets AI agents query and manage your databases directly.
The official MCP TypeScript SDK: the best way to build MCP servers and clients in the JS/TS ecosystem, seamless with the Node stack.
A Chrome-operating MCP: lets AI drive the browser to click, fill forms and screenshot — a lightweight way to automate web operations.
A big curated collection of MCPs for Chinese users: a search-friendly list of MCP servers, the first stop for developers in China.
A broad collection of AI MCP servers: hundreds of servers organized by use case, actively community-maintained. A complementary entry point for finding MCPs.
Connects to 3,000+ pre-built cloud scraping tools (Actors) on the Apify platform, covering websites, e-commerce, social media, search engines and more.
The official MCP Go SDK: write high-performance MCP servers and clients in Go. Great for building production-grade, high-concurrency MCP tools.
The Home Assistant smart-home MCP: lets AI control devices in your home and query their status — build your own AI smart-home hub.
The official MCP C# SDK: the standard way for .NET developers to integrate MCP, covering both servers and clients. Suited to enterprise projects.
One of the earliest MCP server collections: broad coverage with indexes of common browser, database, filesystem and developer-tool servers.
The official MCP Java SDK: build MCP servers and clients in the Java ecosystem, friendly to Spring and other frameworks. A top pick for back-end teams.
A collection of official Microsoft MCP deployment solutions: centralizes MCP integration for multiple Microsoft products, letting agents interop with the Microsoft ecosystem.
A set of MCP adapters and tools: provides MCP integration adapters for common applications, lowering the barrier to building servers and ecosystem integration yourself.
An MCP app store: packages MCP servers and clients into one-click installable products. A distribution platform for the MCP ecosystem.
A curated collection of Claude plugins: gathers plugins, extensions and skills around Claude Code / Copilot to enhance everyday development.
A document-parsing MCP: parses PDF, Word and other document types into structured content — a preprocessing tool before feeding content to AI.
MiniMax's official MCP: a one-stop server that brings image generation, text-to-video, speech and other multimodal capabilities into your AI tools.
The Qdrant vector-database MCP: lets AI operate a knowledge base directly for semantic retrieval — the standard vector storage for RAG applications.
An AI accessibility-testing browser: lets agents automatically run accessibility (a11y) checks on web pages, helping with QA and compliance.
A collection of DevOps-oriented MCP servers: Kubernetes, IaC, monitoring and CI/CD servers, curated for DevOps engineers.