AI MCP Servers
MCP servers extend what AI models can do by providing structured access to external tools, APIs, and data sources. Google Calendar, GitHub, Slack, databases — any service can become an MCP tool.
MCP Server for Z.AI - A Model Context Protocol server that provides AI capabilities
x402 MCP server for AI agent payments. Lets Claude, Cursor, LangChain and CrewAI pay for HTTP 402–gated APIs with USDC micropayments on Base L2. Non-custodial, 0% fee. Unlike Cloudflare Pay-Per-Crawl, works on any host and settles directly on-chain.
MCP server for interacting with Datadog API
Vapi MCP Server
MCP server for Upstash
MCP server for Context7
MCP server for SAPUI5/OpenUI5 development
A Salesforce connector MCP Server.
Shared infrastructure for Transcend MCP Server packages
MCP (Model Context Protocol) Instrumentation
Theia - MCP Server
ClickUp MCP Server - Powering AI Agents with full ClickUp task, document, and chat management capabilities.
Superblocks MCP server
MCP server for interacting with Supabase
'Slite MCP server'
MCP server for interacting with Slack
Serper MCP Server supporting search and webpage scraping
Sentry MCP Server
SAP Fiori - Model Context Protocol (MCP) server
MCP Server for interacting with Salesforce instances
Self-learning vector database for Node.js — hybrid search, Graph RAG, FlashAttention-3, HNSW, 50+ attention mechanisms
MCP Server for Asana
Remotion's Model Context Protocol
ModelContextProtocol server for Ref
Official Railway MCP server
MCP server for project-local RAG memory with knowledge graph and multilingual vector search
Experimental MCP server for browser automation using Puppeteer (inspired by @modelcontextprotocol/server-puppeteer)
A Model Context Protocol server implementation for Nx
Official MCP server for Notion API
Next.js development tools MCP server with stdio transport
AI agent orchestration framework for TypeScript/Node.js - 27 adapters (LangChain, AutoGen, CrewAI, OpenAI Assistants, LlamaIndex, Semantic Kernel, Haystack, DSPy, Agno, MCP, OpenClaw, A2A, Codex, MiniMax, NemoClaw, APS, Copilot, LangGraph, Anthropic Compu
Integration between n8n workflow automation and Model Context Protocol (MCP)
MongoDB Model Context Protocol Server
MCP server for filesystem access
The one and only MCP Server for dads jokes.
Middy middleware for Model Context Protocol server
TypeScript runtime and CLI for connecting to configured Model Context Protocol servers.
MCP server for interacting with Kubernetes clusters via kubectl
Code Runner MCP Server
mcp server
Model Context Protocol server for Obsidian Vaults
Local RAG MCP Server - Easy-to-setup document search with minimal configuration
MCP server for HyperspaceDB - high performance multi-geometry vector database
A simple Hello World MCP server
Framework for building Model Context Protocol (MCP) servers in Typescript
GitHub Action for evaluating MCP server tool calls using LLM-based scoring
Plug and play auth for Model Context Protocol (MCP) servers
Mapbox MCP server.
Intelligent CLI tool with AI-powered model selection that analyzes your hardware and recommends optimal LLM models for your system
LangChain.js adapters for Model Context Protocol (MCP)
Model Context Protocol (MCP) server for Kubernetes and OpenShift
An MCP server that exposes OpenAPI endpoints as resources
MCP Server for developers building HubSpot Apps
Server-Sent Events transport for Hono and Model Context Protocol
Heroku Platform MCP Server
Gmail MCP server with auto authentication support
ModelContextProtocol server for Figma
Model Context Protocol servers for Playwright
MCP server for ESLint
Official MCP server for esa.io - STDIO transport version
Model Context Protocol (MCP) server for Dynatrace
Currents MCP server
Coinbase Design System - MCP Server
MCP server wrapper for OpenAI Codex CLI
Ultra-simple code search tool with Jina embeddings, LanceDB, and MCP protocol support
MCP server for interacting with Cloudflare API
MCP server for Chrome DevTools
MCP server for accessing LSP functionality
Model Context Protocol (MCP) server for AI-assisted development of CAP applications.
BrowserStack's Official MCP Server
Azure MCP Server - Model Context Protocol implementation for Azure
MCP server for interacting with Azure DevOps
Apify MCP Server
MCP server for using the AMap Maps API
Aikido MCP server
AI Credit Card: Give your AI Agents autonomous virtual credit cards (Mastercard) via Stripe Issuing to pay for APIs and SaaS. x402 & MPP compatible.
Analytics SDK for Model Context Protocol Servers
Core memory palace engine for AgentRecall
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
CowAgent (chatgpt-on-wechat) 是基于大模型的超级AI助理，能主动思考和任务规划、访问操作系统和外部资源、创造和执行Skills、通过长期记忆和知识库不断成长，比OpenClaw更轻量和便捷。同时支持微信、飞书、钉钉、企微、QQ、公众号、网页等接入，可选择OpenAI/Claude/Gemini/DeepSeek/ Qwen/GLM/Kimi/LinkAI，能处理文本、语音、图片和文件，可快速搭建个人AI助理和企业数字员工。
Convert documentation websites, GitHub repositories, and PDFs into Claude AI skills with automatic conflict detection
📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, DeepSeek, Perplexity, Gemini, Gemma, Llama, Grok, and more.
MCP for xiaohongshu.com
本项目为xiaozhi-esp32提供后端服务，帮助您快速搭建ESP32设备控制服务器。Backend service for xiaozhi-esp32, helps you quickly build an ESP32 device control server.
This is MCP server for Claude that gives it terminal control, file system search and diff file editing capabilities
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors
Build autonomous AI agents in Python.
Trigger.dev – build and deploy fully‑managed AI agents and workflows
Local knowledge graph for Claude Code. Builds a persistent map of your codebase so Claude reads only what matters — 6.8× fewer tokens on reviews and up to 49× on daily coding tasks.
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
Java 面试 & 后端通用面试指南，覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发
Installable GitHub library of 1,400+ agentic skills for Claude Code, Cursor, Codex CLI, Gemini CLI, Antigravity, and more. Includes installer CLI, bundles, workflows, and official/community skill collections.
⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。
🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, distributed swarm intelligence, RAG integration, and native Claude Code / Codex Integration
A collection of MCP servers.
🚀 The fast, Pythonic way to build MCP servers and clients.
A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
[EMNLP 2025 Demo] PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译，支持 Google/DeepL/Ollama/OpenAI 等服务，提供 CLI/GUI/MCP/Docker/Zotero
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
What are AI MCP Servers?
MCP (Model Context Protocol) servers give AI models standardized access to external tools and data sources. Instead of building custom integrations for every AI application, MCP provides a universal protocol: any MCP client (Claude, Cursor, Zed) can connect to any MCP server (GitHub, Slack, databases, APIs). Think of it as USB-C for AI — one standard connector that works everywhere.
How to Choose
Evaluate MCP servers on four dimensions: tool coverage (what actions can it perform?), authentication (how does it handle API keys and permissions?), transport type (stdio for local, SSE/HTTP for remote), and maintenance status (is it actively updated?). For data sources, check read vs. write support. For API wrappers, check rate limit handling.
Key Capabilities to Evaluate
Common Patterns
Local process communication. The MCP server runs as a child process of the client. Best for desktop apps and local tools.
Remote server communication. The MCP server runs as a web service. Best for shared, always-on integrations.
Multiple MCP servers combined — e.g., GitHub MCP + Slack MCP + Database MCP give the model access to code, communication, and data.
The model subscribes to changes in MCP resources, enabling reactive workflows.
What to Watch Out For
Top Capabilities
Browse all →Analyzes selected code or entire files and generates natural language explanations of what the code does, how it works, and why certain patterns were chosen. The feature can produce documentation in multiple formats (docstrings, comments, markdown) and supports various documentation styles (JSDoc, Sphinx, etc.). Developers can request explanations at different levels of detail (high-level overview, line-by-line breakdown, architectural context) through the chat interface, with responses appearing as formatted text or code comments.
Translates non-English speech directly to English text using the same Transformer encoder-decoder architecture by prepending a 'translate' task token during decoding, bypassing explicit transcription. The AudioEncoder processes mel spectrograms identically to transcription, but the TextDecoder generates English tokens directly from audio embeddings. This end-to-end approach avoids cascading errors from intermediate transcription-then-translation pipelines and enables language-agnostic audio understanding.
Detects the spoken language in audio by analyzing the AudioEncoder embeddings and using the TextDecoder to predict a language token before generating transcription text. Language detection is implicit in the multitask training; the model learns to identify language from acoustic features without a separate classification head. Supports 99 languages with varying confidence based on training data representation (English: 65% of training data, others: 0.1-2%).
Maintains conversation history within a single chat session, allowing developers to ask follow-up questions, request refinements, and build on previous responses without re-providing context. The extension manages conversation state (messages, responses, context) and sends the full conversation history to ChatGPT's API with each request, enabling contextual understanding of refinement requests like 'make it faster' or 'add error handling'.
Generates new code snippets based on natural language descriptions by sending the user's intent and current editor selection context to OpenAI's API, then inserting the generated code at the cursor position or displaying it in the sidebar. The extension reads the active editor's selected text to provide code context, enabling the model to generate syntactically appropriate code for the detected language. Generation is triggered via keyboard shortcut (Ctrl+Alt+G), command palette, or toolbar button.
Generates docstrings, comments, and API documentation for functions, classes, and modules by analyzing code structure and semantics using GPT-4o. The extension detects function signatures, parameter types, and return types, then generates documentation in multiple formats (JSDoc, Python docstrings, Javadoc, etc.) matching the language and project conventions. Generated docs are inserted inline with proper indentation and formatting.
Analyzes staged or modified code changes in the current Git repository and generates descriptive commit messages using the configured AI provider. The feature integrates with VS Code's Git context to identify changed files and diffs, then sends this information to the AI model to produce commit messages following conventional commit formats or project-specific conventions. This automation reduces the cognitive load of writing commit messages while maintaining code quality and repository history clarity.
Offers a freemium pricing structure where basic problem detection and explanations are available for free, with premium features (likely advanced fix generation, priority support, or higher API quotas) available through paid subscription. The free tier includes GNN-based problem detection and LLM-powered explanations using Metabob's default backend, while premium tiers likely unlock OpenAI ChatGPT integration, higher analysis quotas, or team features. Pricing details are not publicly documented in the marketplace listing.
Browse Other Types
Autonomous AI systems that act on your behalf
ModelsFoundation models, fine-tunes, and specialized AI models
RepositoriesOpen-source AI projects on GitHub
APIsProgrammatic endpoints for AI capabilities
ExtensionsBrowser and IDE extensions powered by AI
WorkflowsAutomation sequences and AI pipelines
View all 14 types →Frequently Asked Questions
What is the Model Context Protocol (MCP)?
MCP is an open protocol that standardizes how AI models connect to external tools and data sources. It defines a common interface for tools (functions the model can call), resources (data the model can reference), and prompts (templates for common tasks). Any MCP-compatible client can connect to any MCP server.
Which AI models support MCP?
Claude (via Claude Desktop and Claude Code), Cursor, Zed, Windsurf, and a growing number of AI applications support MCP. The protocol is open-source and maintained by Anthropic, with community implementations for other platforms.
How do I build an MCP server?
MCP servers can be built in any language. The official TypeScript and Python SDKs are the fastest path. A minimal server defines tools with input schemas and handler functions, then exposes them over stdio or HTTP transport. The MCP specification at modelcontextprotocol.io has the full reference.