"How to interact with MySQL" matching MCP servers:

An MCP server that provides read-only access to MySQL databases.

Enables interaction with MySQL databases (including AWS RDS and cloud instances) through natural language. Supports database connections, query execution, schema inspection, and comprehensive database management operations.

A universal interface that enables AI Agents to seamlessly communicate with Adb MySQL databases, allowing them to retrieve database metadata and execute SQL operations.

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.

Enables agents to pull compact MySQL row diffs into their context, supporting before/after changes via triggers or watermark-based updates, with tools to fetch and acknowledge changes.

A server that enables AI models to interact with MySQL databases through a Model Control Protocol, providing tools for table creation, schema inspection, query execution, and data retrieval.

Enables Claude to interact with a MySQL database by automatically discovering its schema and retrieving full table data for analysis.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A TypeScript MCP server that provides secure, read-only access to a locally hosted MySQL database for AI-agent workflows, with configurable policies and support for multiple MCP clients.

Natural language to SQL engine with multi-connector support (PostgreSQL, MySQL, Snowflake, BigQuery, DuckDB), document QA, semantic caching, and self-hosted MCP server.

Read-only MCP server that lets AI agents safely query SQLite, PostgreSQL, and MySQL/MariaDB. Enforces read-only transactions with column masking, row caps, query timeouts, EXPLAIN-based cost rejection, and rate limiting.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables AI agents to securely query databases (PostgreSQL, SQLite, MySQL, DuckDB) with read-only defaults and multi-layer SQL injection prevention.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Enables AI agents to interact with Amazon Redshift databases using natural language to execute queries, explore schemas, and retrieve sample data.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

MCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.

Connects AI clients to MindsDB via the MySQL protocol to execute SQL queries, manage databases, and perform semantic searches within knowledge bases. It enables automated workflows through job scheduling and provides seamless integration with external data sources.

Enables AI agents to interact with Amazon Redshift databases using natural language to execute queries, list tables, describe schemas, and retrieve sample data.

Enables AI agents to interact with the AI-Archive platform for research paper discovery through semantic search, paper submission and management, peer review with structured scoring, and citation generation in multiple formats.