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618,919 tools. Updated 2026-09-28 11:19

"Natural Language to SQL Conversion and Executing MySQL Queries to Retrieve Data" matching MCP tools:

  • Converts natural language questions into SELECT SQL queries for specified databases, enabling intuitive data retrieval without manual query writing.
    Apache 2.0
  • Ask natural-language questions about the ledger and receive free-form answers. Maps plain queries to structured filters for read-only reporting.
    MIT
  • Search memories using natural language queries to retrieve relevant preferences, decisions, and patterns from past sessions.
    MIT
  • Inspect database schemas and tables for a specific workload without executing SQL. Provide team and workload IDs to review structure and plan queries.
    MIT

Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.
    AGPL 3.0
  • A
    license
    Not graded
    quality
    C
    maintenance
    MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.
    MIT

Matching MCP Connectors

  • Convert any webpage to clean LLM-ready markdown, extraction-first, with article and news modes.

  • Turn any webpage into structured JSON with CSS-selector schemas - strings select text, attributes

  • Execute read-only SQL queries against PostgreSQL, MySQL, or SQL Server. Automatically adapts syntax to the target dialect. Returns results with connection and dialect metadata. Default limit 100 rows.
    MIT
  • Run SQL queries with role-based permissions, enforcing read, write, and delete restrictions across PostgreSQL, MySQL, and SQLite databases.
    MIT
  • Search WormBase for genes, proteins, phenotypes, strains, and other biological entities using natural language queries or specific IDs.
    MIT
  • Retrieve the archive database schema, including table and column names. Understand available data for crafting SQL queries.
    Apache 2.0
  • Process natural language queries to obtain structured data on leads, contacts, and opportunities. Supports table, natural, or combined response formats.
    MIT
  • Converts natural language queries into multi-step SQL analysis plans and executes them against databases to answer complex analytical questions.
    MIT
  • Execute SQL queries in Adb MySQL Cluster to retrieve data, update records, or perform database operations through the MCP server interface.
    Apache 2.0
  • Scan SQL queries for injection, destructive operations, and PII extraction before execution. Blocks unsafe queries; allows safe ones. Use for LLM-generated or user-input SQL.
    Apache 2.0
  • Execute data modification SQL statements (INSERT, UPDATE, DELETE, DDL). Validate without executing by setting dryRun=true; confirm destructive operations like DROP or TRUNCATE before execution.
    MIT
  • Turn natural-language questions into executed SQL queries against a database, returning results, row counts, and self-correcting errors while exploring the schema.
    MIT
  • Learn the basic syntax, common operations, and best practices for WCPS queries. Use this crash course before executing queries to ensure correct and efficient code.
    MIT
  • Execute SQL SELECT queries on MySQL, Oracle, GaussDB, and DM8 databases with configurable row limits and database selection.
    MIT