"A tool that can connect to MySQL database, understand table structure and query related data" matching MCP servers:

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.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

An MCP server that provides access to Garmin Connect fitness, health, and training data through 61 specialized tools. It enables users to query activities, sleep metrics, and performance stats directly within AI clients like Claude or Cursor.

Loads CSV files into a temporary SQLite database and provides comprehensive data analysis tools via MCP, enabling AI assistants to query, analyze, and export data using natural language.

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.

MCP server providing a single query tool to execute SQL against GetDot Database, enabling schema discovery, data loading, and querying via natural language.

Enables inspecting local PDFs and extracting tables into CSV, XLSX, or JSON with options for pages, merging, OCR, engine selection, headers, merged cells, regions, and columns.

A Model Context Protocol server that integrates Garmin Connect data with LLMs to provide personalized running analysis and training plans. It enables users to monitor performance metrics, manage training loads, and receive data-driven workout suggestions based on health indicators like VO2 Max and recovery status.

Enables AI agents to discover official public data sources, inspect their metadata and endpoint parameters, and execute live queries through a unified response envelope with a 500 ms budget.

MCP server for App Store Connect that enables reading app/version data, analytics reports, sales/finance reports, and safely preparing metadata updates via natural language.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

Paid remote MCP endpoint for AI SDK data queries, offering structured JSON tools, token-based access, usage receipts, and audit-ready workflow evidence.

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.

Enables users to query Google Search Console and Bing Webmaster data, inspect indexed URLs, submit same-host URLs to IndexNow, and retrieve PageSpeed Insights and CrUX metrics through their MCP client using their own credentials.

An MCP server for dataset exploration and analysis, enabling LLM clients to perform summary, correlation, distribution, missing value analysis, data cleaning, and statistical tests directly on CSV files.

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

Enables AI assistants to query and interact with Treasure Data through a secure interface, supporting SQL queries, database exploration, CDP segment management, and workflow monitoring across multiple regions.

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 AI agents to interact with over 50 SQL and NoSQL databases through MCP tools for querying, schema inspection, and table management.

A Model Context Protocol server for data wrangling that provides standardized interfaces for data preprocessing, transformation, and analysis tasks including data aggregation and descriptive statistics.

Provides a read-only MCP interface to locally synchronized Amazon seller data, enabling AI agents and analytics tools to query order, inventory, advertising, and settlement information with completeness and freshness checks for safe analysis.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

Enables users to import, query, edit, audit, and export local personal records through schema-driven MCP tools while masking sensitive fields by default.

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

Enables AI assistants and agents to query exchange hours, futures expiries and roll calendars, settlement and FX sessions, DST gaps, Treasury yield curves, ECB FX rates, and CFTC positioning through paid x402 calls, while offering free catalog and listing helpers.

Lets MCP clients safely investigate live business data across multiple enterprise APIs by giving each subject a consistent scoped pseudonym and surfacing disagreements between sources as findings.

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

Enables AI agents and MCP clients to heuristically parse multi-column document dumps, aligned spacing, and CSV/TSV input, converting them into clean GitHub Flavored Markdown tables and typed JSON. Runs fully offline on the Python standard library with zero external dependencies, returning deterministic results without LLM round-trips.

Enables AI agents and MCP clients to convert ASCII/OCR text dumps, aligned spacing, and CSV/TSV data into clean GitHub Flavored Markdown tables and typed JSON deterministically.