"Information about SQL (Structured Query Language)" matching MCP servers:

An enhanced MCP server that enables users to interact with NotebookLM while ensuring strict source fidelity and citation accuracy through client-side prompt structuring. It guides Claude to transform user queries into structured prompts that prevent the addition of external knowledge during document analysis.

A read-only MCP server for SQL Server and PostgreSQL that enables exploring and querying databases (schemas, tables, views, procedures, indexes, foreign keys) and running arbitrary SELECT queries.

A TypeScript Model Context Protocol (MCP) server to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection.

A Model Context Protocol (MCP) server that converts natural language queries into SQL statements, allowing users to query MySQL databases using conversational language instead of writing SQL code.

An MCP server and CLI tool that transforms codebases into AI-ready context through semantic search, call graph analysis, and incremental indexing. It enables AI assistants to perform hybrid vector and keyword searches to understand complex repository structures and cross-file relationships.

MCP server for managing and retrieving reusable SQL templates with semantic search, enabling a workflow of generation, retrieval, and templating.

A governed SQL gateway that exposes typed tools to AI agents, compiling safe read-only queries from a semantic layer while blocking PII before execution, supporting SQL Server, Postgres, and SQLite.

Provides a read-only PostgreSQL SQL surface for LLM agents via MCP, with defense-in-depth security layers for safe database queries.

Cross-platform MCP server for SQL Server that enables AI assistants to explore schemas, relationships, and run read-only queries via natural language.

Enables natural language and SQL querying across SQLite, MySQL, PostgreSQL, and MongoDB databases with support for bulk operations and schema inspection. It features a safety mechanism requiring explicit user confirmation for destructive actions like data modification and deletion.

Enables agents to perform controlled enterprise data queries through semantic intent, with runtime validation of statistics, filters, granularity, permissions, and physical bindings. Exposes tools like semantic_query for safe, fail-closed access to data horizons and capabilities.

Enables querying a PostgreSQL database using natural language by retrieving context from Azure AI Search and generating SQL with Azure OpenAI, with validation and optional execution.

Enables AI assistants to interact with SQL Server Data Warehouses using natural language for automatic schema discovery and report generation. It ensures security by restricting operations to read-only SELECT queries through both code validation and database permissions.

Connects Microsoft Copilot Studio to Azure SQL Databases, enabling natural language interactions for data querying, record management, and schema inspection. It features 12 specialized tools for performing CRUD operations, executing SQL queries, and generating data visualizations like charts.

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.

MCP server enabling natural-language querying of SQLite databases via schema discovery, GraphRAG retrieval, and safely guarded read-only SQL execution.

Enables semantic search and retrieval over local Markdown/MDX documentation using Node.js-based embeddings. Supports multi-language documentation with offline vector indexing and MCP tool exposure for AI assistants.

A FastMCP server that provides natural language interaction with MS SQL databases, enabling users to query data, list tables, describe structures, and execute database operations through a conversational AI interface.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

A Model Context Protocol (MCP) server that provides read-only TDengine database queries for AI assistants, allowing users to execute queries, explore database structures, and investigate data directly from AI-powered tools.