"Understanding SQL Server Schema and Querying" matching MCP servers:

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

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.

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 MCP server that exposes OpenAPI schema information to LLMs like Claude. This server allows an LLM to explore and understand large OpenAPI schemas through a set of specialized tools, without needing to load the whole schema into the context

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.

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

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.

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.

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

A Model Context Protocol server that provides read-only access to PostgreSQL databases with enhanced multi-schema support, allowing LLMs to inspect database schemas across multiple namespaces and execute read-only queries while maintaining schema isolation.

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.

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

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.

Enables querying an Azure SQL Products table via MCP, allowing integration with Microsoft Foundry agents for data retrieval.

Provides LLM access to Exasol database via MCP tools, including metadata reading and data queries, with an optional on-premise text-to-SQL (Governed SQL) translation.

Indexes GraphQL schemas using embeddings to enable semantic search of types and fields for fast lookup. It allows LLMs to discover relevant schema signatures and execute queries against live GraphQL endpoints.

An MCP server for MySQL databases that enables schema exploration, query execution, and resource access through a unified interface. It features a LangGraph-based agent that translates natural language into SQL queries with automatic error recovery and schema discovery.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.