MCP Servers
The open registry for Model Context Protocol servers. Find the right tools, resources, and prompts for your AI agents — filtered by category, transport, or use case.
Servers
160
Tools
465
Categories
11
Contributors
142
MCP server for Exa's neural search API. Provides AI agents with powerful web search capabilities using embeddings-based semantic search. Returns clean, parsed content from web pages with relevance scoring. Supports filtering by domain, date range, and content type for precise information retrieval from the internet.
MCP server for Tavily's AI-optimized search engine. Designed specifically for LLM agents and RAG applications, providing concise, factual search results with source attribution. Supports general web search, news search, and direct Q&A extraction. Returns pre-processed content optimized for AI consumption with relevance scoring and content deduplication.
Skills vs MCP servers
what's the difference?Skillsthe “what to do”
A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.
MCP serversthe “how to connect”
An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. MCP adds connections and actions, not task instructions.
Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.
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