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MCP Encyclopedia

30 servers

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.

Quick start (using Claude Desktop as an example):

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.

Guides

Essential Guides

Featured MCP Servers

Star counts as of the 2026-09-02 snapshot

178k

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.

#Microsoft official#Document conversion#Markdown
GitHub ↗

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.

#Web access#Search#Information retrieval
GitHub ↗

A context-optimization layer for LLM applications that automatically manages the context window — dramatically improving agent performance in long conversations and large codebases.

#Context management#Performance
GitHub ↗

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.

#Codebase#Knowledge graph#Programming
GitHub ↗
36.7k

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.

#Microsoft official#Browser#Automation
GitHub ↗

The official GitHub MCP server: lets AI agents directly manage repositories, PRs and issues. A core component of developer automation workflows.

#GitHub official#Repository management#Must-have for devs
GitHub ↗

Lets AI command Blender through natural language for 3D modeling, scene creation and editing. A flagship project for creating 3D assets with prompts.

#Blender#3D modeling#Creative tool
GitHub ↗

A lightweight cross-platform database client at just 20MB, with built-in MCP support that lets AI agents query and manage your databases directly.

#Database#Lightweight tool
GitHub ↗

A Chrome-operating MCP: lets AI drive the browser to click, fill forms and screenshot — a lightweight way to automate web operations.

#Browser#Automation#Chrome
GitHub ↗

Connects to 3,000+ pre-built cloud scraping tools (Actors) on the Apify platform, covering websites, e-commerce, social media, search engines and more.

#Web scraping#Data extraction#Cloud tools
GitHub ↗

A collection of official Microsoft MCP deployment solutions: centralizes MCP integration for multiple Microsoft products, letting agents interop with the Microsoft ecosystem.

#Microsoft official#MCP#Enterprise
GitHub ↗
2.2k

A set of MCP adapters and tools: provides MCP integration adapters for common applications, lowering the barrier to building servers and ecosystem integration yourself.

#Adapters#Integration#Tools
GitHub ↗

An MCP app store: packages MCP servers and clients into one-click installable products. A distribution platform for the MCP ecosystem.

#App store#Distribution#Ecosystem
GitHub ↗

A document-parsing MCP: parses PDF, Word and other document types into structured content — a preprocessing tool before feeding content to AI.

#Document parsing#PDF#Preprocessing
GitHub ↗

MiniMax's official MCP: a one-stop server that brings image generation, text-to-video, speech and other multimodal capabilities into your AI tools.

#Multimodal#Official#Image & video gen
GitHub ↗

The Qdrant vector-database MCP: lets AI operate a knowledge base directly for semantic retrieval — the standard vector storage for RAG applications.

#Vector database#RAG#Knowledge base
GitHub ↗

An AI accessibility-testing browser: lets agents automatically run accessibility (a11y) checks on web pages, helping with QA and compliance.

#Accessibility#Browser#QA
GitHub ↗