Category · MySQL & database MCP servers
MySQL MCP Server and the Best Database MCPs in 2026
A MySQL MCP server lets an AI agent explore your schema, write queries and read results without you pasting table definitions into a chat window. In 2026 the community MySQL servers have matured enough for daily use, and the same pattern now covers Postgres, SQLite, MongoDB, ClickHouse and the managed warehouses. This page covers the MySQL options and the safety decisions that separate a useful setup from a dangerous one.
What this category covers
Database MCP servers expose a database connection as a set of tools: list tables, describe a schema, run a query, and in some cases write data. The value is that the agent discovers your schema itself rather than working from a description you wrote by hand, which is where most AI-generated SQL goes wrong. MySQL servers in this category are community-maintained rather than vendor-official, so the important variable is what permissions you hand the connection. For the wider relational picture, see our SQL MCP server guide at /category/sql-mcp-server.
The servers worth wiring up
For MySQL, the widely used community MySQL MCP server covers schema inspection and query execution over a standard connection string. If your stack is Postgres, the official PostgreSQL MCP server is read-only by design and the safest starting point — our Postgres MCP server page at /category/postgres-mcp-server goes deeper. SQLite MCP is ideal for local analysis and prototyping. MongoDB MCP handles document stores with aggregations and index management. ClickHouse MCP and Snowflake MCP cover analytics warehouses. Supabase MCP is the right pick when you want tables, auth users, storage and edge functions in one server rather than a raw database connection.
Buying guide
Create a dedicated database user for the agent and grant it the least privilege that makes the task possible. Read-only is the correct default, and for MySQL that means SELECT on specific schemas rather than a general account. Point the agent at a replica rather than primary where you have one. Set a query timeout and a row limit, because an agent exploring an unfamiliar schema will eventually write an unbounded join. Finally, prefer servers that expose schema discovery as a separate tool from query execution, so the model can learn the structure before it writes SQL. For the rest of a working setup, see the best MCP servers for developers at /best-mcp-servers-for-developers.
The Tools, Ranked
A community-maintained MCP server that connects AI agents to MySQL over a standard connection string, exposing schema discovery, table description and query execution. Configure with a least-privilege database user.
A read-only Postgres MCP server that lets the model explore schema and run queries without write access. The safest database server to start with.
A lightweight SQLite MCP server, perfect for local analytics and prototyping where the whole dataset fits in a single file.
The official MongoDB server giving agents read and write access to collections, aggregations and index management. Works with Atlas and self-hosted deployments.
Secure read-only SQL querying and schema exploration for ClickHouse clusters, supporting both cloud and self-hosted deployments for natural-language analytics.
Talk to a Supabase project — tables, auth users, storage and edge functions — from an AI model, rather than managing a raw database connection.
Connects assistants to Snowflake for SQL execution, schema exploration and Cortex AI functions, so agents can answer analytical questions against governed warehouse data.
Key-value operations for agents — get, set, delete, expire, pub/sub and stream reads — useful for shared state and cache inspection alongside a relational database.