What is MCP (Model Context Protocol)?

MCP (Model Context Protocol) is an open-source standard created by Anthropic that enables AI applications like Claude and ChatGPT to connect to external tools, data sources, and services. Think of it like a USB-C port for AI—a universal connector that lets AI models plug into various tools and databases in a consistent, standardized way.

MCP works through three main components: MCP Hosts (AI applications like Claude Desktop), MCP Clients (connectors within the host that communicate with servers), and MCP Servers (external services that provide data and tools). When you ask an AI to perform a task requiring external data, the client discovers available tools, sends requests to the appropriate server, and returns results to the AI.

What can MCP servers do?

MCP servers can connect AI to virtually any external system. Common capabilities include: accessing databases and file systems, integrating with tools like GitHub, Slack, and Notion, executing code and running tests, managing cloud infrastructure, scraping web data, and automating workflows. Each server exposes specific tools the AI can use during conversations.

MCP is used by developers, enterprises, and AI enthusiasts who want to extend AI capabilities. Major AI providers including OpenAI, Google DeepMind, and Anthropic support MCP. It's particularly popular among developers building AI agents, companies creating enterprise knowledge assistants, and teams automating complex workflows.

How do I install an MCP server?

MCP servers can be installed in AI applications like Claude Desktop or Cursor. Typically, you add the server configuration to your app's settings file (like claude_desktop_config.json), specifying the server command and any required environment variables. Many servers are available via npm or can be run directly from their GitHub repositories.

MCP includes built-in security features like authentication specs and permission controls. However, as with any integration, you should review server code before installation, use environment variables for sensitive credentials, only install servers from trusted sources, and follow the principle of least privilege when granting permissions.

What's the difference between MCP and regular APIs?

While MCP uses APIs under the hood, it's specifically designed for AI context. Regular APIs serve general web applications, while MCP provides a standardized interface that AI models can discover and use autonomously. MCP servers are tool-agnostic, schema-driven, and reusable across different AI agents without custom integration code.

Can I build my own MCP server?

Yes! MCP provides SDKs in TypeScript, Python, C#, Java, and other languages to help you build custom servers. You can create servers that expose your own tools, connect to proprietary systems, or wrap existing APIs in an MCP-compatible interface. The official documentation provides guides and examples to get started.

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Official MCP Servers

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Bright Data

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Empowers AI agents to access, discover, and extract real-time web data, bypassing restrictions and bot detection.

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Firecrawl

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Empowers LLMs with advanced web scraping capabilities for content extraction, crawling, and search functionalities.

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ElevenLabs

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Enables interaction with Text to Speech and audio processing APIs for MCP clients.

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Magic

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Generate modern UI components instantly from natural language descriptions within your IDE.

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Browserbase

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Enables LLMs to control cloud browsers for web interaction, data extraction, and task automation using Browserbase and Stagehand.

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Featured MCP Servers

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Godot

1,673

Enables AI assistants to interact with the Godot game engine by launching the editor, running projects, and capturing debug output.

Excel

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Enables Excel file manipulation capabilities without requiring Microsoft Excel installation.

Unity

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Enables communication between Unity and Large Language Models for automating workflows and controlling the Unity Editor.

FastAPI

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Exposes FastAPI endpoints as Model Context Protocol (MCP) tools with zero configuration.

Ghidra

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Enables Large Language Models (LLMs) to autonomously reverse engineer applications by exposing Ghidra's core functionality through an Model Context Protocol (MCP) server.

Task Master

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Streamline AI-driven development workflows by automating task management with Claude.

Top MCP Servers

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TrendRadar

45,580

Aggregates trending topics from over 35 platforms, offering intelligent filtering, automated multi-channel notifications, and AI-powered conversational analysis for deep news insights.

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Superpowers

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Empowers AI coding agents with a comprehensive and structured software development workflow, from design refinement to TDD-driven implementation.

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Context7

44,852

Fetches up-to-date documentation and code examples for LLMs and AI code editors directly from the source.

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MindsDB

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Build AI applications that can learn and answer questions over large-scale federated data sources using a federated query engine.

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Playwright

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Automates browser interactions for Large Language Models (LLMs) using Playwright.

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GitHub

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Enables advanced automation and interaction capabilities with GitHub APIs for developers and tools using the Model Context Protocol.

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Cargo-Cross-Check

Checks Rust projects across multiple platforms and targets simultaneously within a single editor session.

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Stitch

Proxies Google Stitch API calls, providing resilient screen generation and automatic gcloud authentication.

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Rival

Access comprehensive AI model comparison data from rival.tips within your AI coding assistant.

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Wbgapi360

Provides an enterprise-grade async Python client for the World Bank Data360 API, facilitating data retrieval and analysis for both human users and AI agents.

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XHS Vision

Generates high-quality, Xiaohongshu-style portrait images with customizable aesthetics and feature locking for consistent character representation.

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IcoGenie

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MCP Clients

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Zed

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Edit code with high performance and multiplayer collaboration.

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Cline

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Automates coding tasks directly within your IDE using AI, capable of creating/editing files, executing commands, and using the browser with user permission.

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