MySQL MCP Server is an open-source Model Context Protocol server that provides AI assistants with secure, structured acc
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Tracked since2026
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Entry price
Free, no paid tier
Biggest pro
Strong security defaults, read-only by default with granular write permissions
Biggest con
No built-in support for stored procedures or MySQL-specific features like events
TL;DR - MySQL MCP Server
- Open-source MCP server giving AI assistants secure read/write access to MySQL databases
- Inspects schemas, executes queries with prepared statements, and analyzes execution plans
- Read-only by default with granular write permissions, works with Claude, Cursor, and VS Code
Pricing: Free forever
Best for: Individuals & startups
What is MySQL MCP Server?
MySQL MCP Server is an open-source Model Context Protocol server that provides AI assistants with secure, structured access to MySQL databases. It enables LLMs like Claude to inspect database schemas, execute SQL queries, and analyze data through a controlled interface with built-in safety mechanisms.
The server exposes database tables as MCP resources with full schema information including column names, data types, indexes, constraints, and foreign key relationships. Query execution supports read-only SELECT statements by default, with optional write operations (INSERT, UPDATE, DELETE) that can be individually enabled through environment variables. Security features include SQL injection prevention via prepared statements, query whitelisting and blacklisting, rate limiting, query complexity analysis, and connection encryption.
Performance is handled through connection pooling, query result caching, large result set streaming, and execution plan analysis using EXPLAIN and EXPLAIN ANALYZE. The server works with Claude Desktop, VS Code, and other MCP clients, connecting to any MySQL instance through standard environment variable configuration. Multiple implementations exist in both Node.js and Python, making it adaptable to different deployment environments.
Available on: Web
Pros & Cons
Pros
- Strong security defaults, read-only by default with granular write permissions
- Full schema introspection lets AI assistants understand database structure without documentation
- Performance features (pooling, caching, streaming) handle production-scale databases
- Multiple implementations (Node.js, Python) for flexible deployment
- Simple environment variable configuration connects to any MySQL instance
Cons
- No built-in support for stored procedures or MySQL-specific features like events
- Write operations require explicit opt-in, extra configuration for full CRUD workflows
- Community-maintained with multiple forks, no single canonical implementation
- No visual query builder or schema visualization capabilities
Key Features
Database schema inspection with column types, indexes, constraints, and foreign key discoverySQL query execution with read-only mode by default and optional write operationsPrepared statements for SQL injection prevention on all queriesQuery execution plan analysis with EXPLAIN and EXPLAIN ANALYZE supportConnection pooling and query result caching for performance optimizationGranular write control, INSERT, UPDATE, DELETE each enabled independently via env varsLarge result set streaming to handle queries returning substantial dataRate limiting and query complexity analysis for resource protection
Pricing Plans
Pricing checked Jun 20, 2026
Open Source
Free
- Full source code access
- Community support
- Self-hosted
Reviews
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MySQL MCP Server FAQ
Is it safe to connect an AI assistant to a production MySQL database?
The server defaults to read-only mode — only SELECT queries are allowed unless you explicitly enable writes via environment variables (
ALLOW_INSERT, ALLOW_UPDATE, ALLOW_DELETE). Additional safeguards include prepared statements for SQL injection prevention, rate limiting, and query complexity analysis.Which MySQL MCP Server implementation should I use?
The most established is
@designcomputer/mysql_mcp_server (Node.js). A Python implementation from @benborla29/mcp-server-mysql is also available. Both provide schema inspection and query execution. Choose based on your deployment environment and language preference.Can it handle large databases with hundreds of tables?
Yes. The server uses connection pooling, query result caching, and streaming for large result sets. Schema introspection works across all tables, and the AI assistant can discover structure incrementally rather than loading everything into context at once.
Does it support MySQL-compatible databases like MariaDB or PlanetScale?
It connects via standard MySQL protocol, so it works with MariaDB, PlanetScale, TiDB, Amazon Aurora MySQL, and any MySQL-compatible database. Configure the connection using standard
MYSQL_HOST, MYSQL_PORT, MYSQL_USER, and MYSQL_PASSWORD environment variables.Source: github.com