MCP Servers

A directory of curated & open-source Model Context Protocol servers. Search and discover MCP servers to enhance your AI capabilities.

Excalidraw

Excalidraw's official MCP server that streams interactive hand-drawn diagrams to Claude, ChatGPT, and VS Code with smooth camera control and fullscreen editing.

Claude Context Mode

This MCP Server compresses tool outputs by 98% using sandboxed execution, full-text search with BM25 ranking, and multi-language support for Claude Code.

Context+

An MCP server provides AST parsing, semantic search, and feature graph tools for large codebases with 99% accuracy.

Terminal

Give AI agents safe shell access via Terminal MCP, featuring native PTY support, sandbox restrictions, and asciicast session recording.

Cloudflare

Query and execute Cloudflare API calls through an MCP server that solves context overflow with isolated code execution and intelligent truncation.

Comet

An MCP server connecting Claude Code to Perplexity Comet for multi-agent web browsing, research delegation, and authenticated workflows.

Microsoft Work IQ

Query Microsoft 365 tenant data with WorkIQ MCP server. Supports emails, calendar, documents, Teams, and people search through natural language.

Better Icons

Search and sync icons directly to your project files using Better Icons MCP server. Supports React, Vue, Svelte, and 150+ icon collections.

Security Detections

Query security detection rules across Sigma, Splunk ESCU, Elastic, and KQL formats from a single MCP server with MITRE ATT&CK and CVE filtering.

YouTube MCP Server

Connect your AI agent to YouTube with this MCP server. Supports 99 languages, in-memory audio processing, and efficient caching for developers.

SEO Research

Integrate Ahrefs SEO data into your IDE with SEO Research MCP. Check backlinks, traffic, and keywords directly in Cursor, Claude, and VS Code.

Cursor n8n

Control your n8n workflows directly from Cursor IDE. This MCP server enables AI assistants to create, manage, and debug automations via the n8n API.

Apify

Connect AI assistants to 8000+ web scraping tools via Apify MCP Server. Extract social media data, contact details, and automate web research.

Blueprint

Use the Blueprint MCP Server to generate system architecture diagrams directly from your codebase using Nano Banana Pro.

HOPX

Connect your AI agents to secure, isolated cloud environments with the HOPX MCP Server. Execute Python, JS, and Bash safely without local risks.

Code Execution Mode

Reduce MCP context overhead from 30k to 200 tokens. This bridge enables secure, rootless Python code execution and on-demand tool discovery for Claude.

WPMCP

Use the WordPress MCP Server to give AI assistants full control over your site for content, theme, and plugin management.

MATLAB

Install and configure the MATLAB MCP Server for a direct connection between your local MATLAB session and MCP applications like Claude Desktop.

Claude Skills

An MCP server that brings Anthropic's Claude Skills to AI assistants like Cursor AI, featuring local semantic search and a no-timeout architecture.

Codex MCP

Open-source MCP server for OpenAI Codex CLI integration with Claude and Cursor. Features sandboxed operations, structured changes, and cross-platform compatibility.

ImageSorcery MCP

Use the ImageSorcery MCP server to crop, resize, remove backgrounds, and run object detection on local images with your AI assistant.

FAQs

Q: What exactly is the Model Context Protocol (MCP)?

A: MCP is an open standard, like a common language, that lets AI applications (clients) and external data sources or tools (servers) talk to each other. It helps AI models get the context (data, instructions, tools) they need from outside systems to give more accurate and relevant responses. Think of it as a universal adapter for AI connections.

Q: How is MCP different from OpenAI's function calling or plugins?

A: While OpenAI's tools allow models to use specific external functions, MCP is a broader, open standard. It covers not just tool use, but also providing structured data (Resources) and instruction templates (Prompts) as context. Being an open standard means it's not tied to one company's models or platform. OpenAI has even started adopting MCP in its Agents SDK.

Q: Can I use MCP with frameworks like LangChain?

A: Yes, MCP is designed to complement frameworks like LangChain or LlamaIndex. Instead of relying solely on custom connectors within these frameworks, you can use MCP as a standardized bridge to connect to various tools and data sources. There's potential for interoperability, like converting MCP tools into LangChain tools.

Q: Why was MCP created? What problem does it solve?

A: It was created because large language models often lack real-time information and connecting them to external data/tools required custom, complex integrations for each pair. MCP solves this by providing a standard way to connect, reducing development time, complexity, and cost, and enabling better interoperability between different AI models and tools.

Q: Is MCP secure? What are the main risks?

A: Security is a major consideration. While MCP includes principles like user consent and control, risks exist. These include potential server compromises leading to token theft, indirect prompt injection attacks, excessive permissions, context data leakage, session hijacking, and vulnerabilities in server implementations. Implementing robust security measures like OAuth 2.1, TLS, strict permissions, and monitoring is crucial.

Q: Who is behind MCP?

A: MCP was initially developed and open-sourced by Anthropic. However, it's an open standard with active contributions from the community, including companies like Microsoft and VMware Tanzu who maintain official SDKs.

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