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 Neon's serverless PostgreSQL platform. Enables AI agents to manage Neon projects, branches, databases, and roles. Supports creating database branches for development and testing, running SQL queries, managing connection strings, and performing schema migrations. Leverages Neon's instant branching for safe experimentation without affecting production data.
MCP server for the Databricks Data Intelligence Platform. Enables AI agents to run SQL against the Unity Catalog, inspect schemas and tables, and manage and monitor jobs, bringing lakehouse data and workflows into AI-powered development tools.
Apache Solr's MCP server connects agents to search collections and query workflows for schema discovery, relevance investigation, and search application development.
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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