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
92
Tools
343
Categories
11
Contributors
79
MCP server for SQLite database interaction and business intelligence. Enables AI agents to query SQLite databases, create and modify tables, run analytical queries, and generate insights from data. Supports read-write operations with transaction safety and provides schema introspection for understanding database structure.
Official Supabase MCP server for database and backend integration. Enables AI agents to query PostgreSQL databases, manage tables and schemas, handle authentication users, interact with storage buckets, and invoke edge functions. Provides full access to Supabase project management including migrations and type generation.
Connects AI agents to ChromaDB vector databases for semantic search and retrieval augmented generation (RAG) workflows. Supports creating collections, upserting documents with embeddings, querying by semantic similarity, and managing metadata filters. Ideal for knowledge base and document retrieval applications.
Provides AI agents with access to ClickHouse analytical databases through the Model Context Protocol. Enables running analytical queries, exploring table schemas, inspecting materialized views, and monitoring query performance. Designed for OLAP workloads with support for large result sets and query profiling.
MCP server for Airtable that lets AI agents read and write records, list bases and tables, inspect field schemas, and run filtered queries. Ideal for turning Airtable into a lightweight backend or knowledge base that agents can manage conversationally.
Provides read-only access to PostgreSQL databases through the Model Context Protocol. Enables AI agents to inspect database schemas, run SELECT queries, and explore table structures. Designed for safe database exploration with read-only transaction isolation to prevent accidental data modification. Originally part of the reference servers, now archived and available in servers-archived.
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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