"MySQL" matching MCP servers:

Enables LLMs to query and analyze data across multiple MySQL databases with enterprise data federation, intelligent caching, cross-system analytics, and automated schema discovery for comprehensive business intelligence.

Read-only SQL across PostgreSQL, MySQL, S3-compatible buckets and folders of Parquet, CSV and JSON files — and one query can join across all of them, federated in-process by DuckDB. Sources are given as connection strings at startup, and no tool writes: they are absent rather than disabled.

MCP server for Hydra ETL: lets AI assistants write declarative YAML ETL pipelines (CSV, Parquet, PostgreSQL, MySQL, MongoDB, APIs) and validate them before any data is read or written.

Enables AI agents to discover and query data federated across MySQL/MariaDB, PostgreSQL, ClickHouse, S3 and Kafka with SQL, exposing tools to list databases, schemas, tables and connections, describe columns, search objects, inspect table statistics, run EXPLAIN, and execute arbitrary statements. It runs locally over stdio against a PostgreSQL-wire endpoint and returns structured results or SQLSTATE-coded errors.

Enables querying and mutating data across multiple sources (CSV, Google Sheets, SQLite, PostgreSQL, MySQL, MongoDB, Oracle) through a dynamic GraphQL API, with flexible filtering, batching, persisted queries, and dynamic source switching.

Enables agents to interact with MySQL databases securely, supporting multi-database read-only queries, protected DML writes, and streaming exports to Sandbox Datasets.

Enables AI agents to securely connect to and query Microsoft SQL Server databases with read-only access, schema discovery, and relationship mapping. Features advanced security protections, health monitoring, and bulk operations for production environments.

Enables unified access to both structured databases (PostgreSQL, MySQL, SQLite, etc.) and unstructured object storage (AWS S3, Alibaba OSS, Huawei OBS, etc.) through a single interface.

An MCP server for data reconciliation between MySQL and Snowflake, enabling LLM agents to validate data integrity during migrations and ETL processes.

MCP server that syncs and queries comprehensive stock data (quotes, financials, dividends, analyst forecasts, options, news) from Yahoo Finance and Investing.com into an external MySQL database.

Enables AI agents to securely interact with multiple databases (MySQL, PostgreSQL) via natural language queries, with cross-database querying and enterprise-grade security.

MCP server for the OrionBelt Semantic Layer. Enables LLMs to explore governed semantic models, compile YAML metric definitions into optimized SQL across 8 engines (BigQuery, ClickHouse, Databricks, Dremio, DuckDB, MySQL, PostgreSQL, Snowflake), and execute analytics queries via natural language. Works with Claude, Cursor, Windsurf, and Copilot.

Universal Database MCP Server enabling AI assistants to connect and query multiple databases including Databricks, BigQuery, PostgreSQL, MySQL, SQL Server, SQLite, and MariaDB through a unified interface.

Enables LLMs to perform analytical SQL queries on PostgreSQL/MySQL databases via DuckDB, with tools for querying, aggregation, and materialized views.

A versatile tool that enables querying and exporting data from multiple relational databases (MySQL, PostgreSQL, Oracle, SQLite, etc.) in read-only mode for data safety.

Multi-database SQL operations MCP server that enables CRUD, table creation, and data seeding for MySQL, PostgreSQL, and SQLite through natural language.

AI-native data analysis agent as an MCP Server. Connect your Excel files, CSVs, and MySQL databases. Understand business semantics. Query with natural language.

Enables secure interaction with multiple SQL database engines (MySQL, PostgreSQL, SQLite, SQL Server) through a standardized interface. Supports schema inspection, safe query execution, and controlled write operations with built-in security restrictions.

Enables LLM agents to connect to and query many database types—including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift—through a single unified API. It provides schema retrieval and optimized query execution with normalized schemas for easier natural-language-driven data access.

An MCP server that provides a unified interface for connecting LLM agents to many database types, including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift. It exposes schema retrieval and query execution endpoints, normalizing schemas and optimizing LLM-generated queries for compatibility.

Enables LLM agents to connect to and retrieve data from PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift via a unified MCP API, with schema normalization, query optimization, and secure connections.

Enables LLM agents to connect to and retrieve data from multiple database types through a unified API, including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift. Supports schema normalization and query transformation for LLM-friendly database interaction.

Enables LLM agents and AI applications to connect to and retrieve data from multiple database types such as PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift through a unified API with schema normalization and query transformation.

Enables LLM agents to connect to and query multiple database types through a unified API, with schema normalization, query transformation, and support for PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift.

Enables LLM agents to connect to and query multiple database types through a unified API, with schema normalization, query transformation, and support for PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift.

MCP server that parses legacy relational database schemas (Oracle, DB2, MySQL, MSSQL) and transpiles them to PostgreSQL with generated Prisma schema and TypeScript query helpers.

Enables LLM agents to connect to and query many database types—such as PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift—through a single unified API. It normalizes schemas for LLM compatibility and transforms generated queries back into their original form, with SSL support and Docker deployment.

Enables LLM agents to connect to and retrieve data from many database types—including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift—through a single unified API. Provides schema retrieval, query optimization, and query transformation so models can work against normalized layouts across multiple data sources.

Enables LLM agents to connect to and retrieve data from multiple database types through a unified API, with schema normalization, query transformation, and secure connections. Supports PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift.

Enables LLM agents to connect to and retrieve data from a wide range of databases — including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift — through a single unified API. It normalizes schemas and transforms LLM-generated queries so agents can query multiple data sources securely and efficiently.