"Querying data in MySQL" matching MCP servers:

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

Bootstrap MCP server for future data exploration and querying across multiple databases, currently only provides a hello_world tool with no actual data connectivity.

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.

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.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Provides safe, deterministic inspection, transformation, validation, and diffing of structured data (JSON, CSV, YAML, Parquet) via schema-aware MCP tools.

Offline-first MCP server for TwitterAPI.io docs (endpoints, pages, blogs) with fast fuzzy search.

MCP server for CyberQuant data sharing platform that enables AI assistants to directly query and analyze financial data using CSV output for token efficiency.

Provides access to Grips Intelligence e-commerce analytics data through Model Context Protocol. Enables querying domain performance metrics, channel breakdowns, ad spend data, and device analytics for e-commerce businesses.

Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.

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.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

Extracts structured JSON data from unstructured text using predefined schemas for receipts, invoices, resumes, and emails. It allows users to transform messy text into organized data through built-in or custom-defined fields.

模糊匹配两份表格中的公司名称和日期，输出已匹配、待复核和未匹配三种结果，便于数据对账。

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 assistants to upload clinical documents and medical device images for health data extraction, normalization, and retrieval of structured coded results in formats such as JSON, FHIR, HL7, CSV, and Parquet.

Enables querying, inserting, and managing unstructured data in RawTree via SQL, JSON ingestion, and log inspection through MCP clients like Claude Code, Cursor, and Claude Desktop.

Unified MCP server for Arpe.io data tools enabling AI assistants to build, preview, and execute high-performance data commands including database export, transfer, pipeline, and migration.

Exposes Rybbit Analytics as MCP tools for querying site traffic, page views, visitor sessions, and live visitor counts through natural language.

Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.