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

177

Tools

471

Categories

11

Contributors

155

4 servers

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ClickHouse MCP ServerClickHouse

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.

1.6k
Snowflake MCP ServerSnowflake

Official Snowflake MCP server enabling AI agents to query and analyze data in the Snowflake AI Data Cloud. Supports running SQL against warehouses, exploring databases and schemas, describing tables, and invoking Cortex AI services for search and analytics, with role-based access control honored end to end.

980
DuckDB MCP ServerMotherDuck

MCP server for DuckDB, the fast in-process analytical database. Lets AI agents run analytical SQL over local files (CSV, Parquet, JSON), attach databases, inspect schemas, and profile queries. Ideal for ad-hoc data analysis, ETL prototyping, and querying large columnar files without a separate database server.

780
MotherDuck MCP ServerMotherDuck

Official MCP server for DuckDB and MotherDuck. Lets AI assistants run SQL analytics directly against local DuckDB files, in-memory databases, S3-hosted data, and MotherDuck cloud warehouses. Supports read and write queries, browsing database catalogs, and switching between connections on the fly, making it well suited for conversational data exploration and lightweight analytics.

0

Skills vs MCP servers

what’s the difference?

Skillsthe “what to do”

A skill packages know-how — instructions, an example prompt, and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.

MCP serversthe “how to connect”

An MCP server gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transport. 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.

Built an MCP server?

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