"sql server" matching MCP servers:

An MCP server that connects LLMs to SQL databases for development assistance, enabling query execution, schema exploration, and data manipulation while providing safety controls against destructive operations.

An MCP server that connects AI assistants to Microsoft SQL Server databases, enabling schema exploration and read-only queries safely.

A Model Context Protocol server that provides AI assistants with comprehensive access to SQL databases, enabling schema inspection, query execution, and database operations with enterprise-grade security.

Enables interaction with Microsoft SQL Server databases using both SQL Server and Windows Authentication. It supports flexible connection configurations, including read-only modes and encrypted communication for secure data management.

Enables read-only querying and diagnostics for dual SQL Server 2019 instances with rate limiting and security controls, accessible via MCP tools over HTTP.

Enables querying and managing PostgreSQL and MySQL databases through natural language, supporting connection management, query execution, schema inspection, and parameterized queries with connection pooling.

A Model Context Protocol server that enables AI assistants (Cursor, Windsurf, Claude Code) to interact with Microsoft SQL Server databases by providing connectivity through environment-configurable connections.

An MCP server for Microsoft SQL Server integration that enables users to query, monitor, and analyze databases directly through Claude. It supports schema exploration, performance analysis, and optional write operations via natural language commands.

A Model Context Protocol server that allows Large Language Models like Claude to execute SQL queries, explore database schemas, and maintain persistent connections to SQL Server databases.

Enables secure database operations on SQL Server instances through a three-tier safety system, supporting schema exploration, query execution, performance analysis, and data export with configurable security levels from read-only to full development access.

Provides direct SQL query access to Microsoft SQL Server databases with full CRUD operations, enabling AI assistants to execute queries, modify data, and manage database objects through a simplified interface.

Enables AI assistants to interact with SQL Server databases through natural language, providing capabilities for executing queries, exploring schemas, analyzing performance, backing up tables, and managing data with built-in safety limits.

A Model Context Protocol server that enables secure interaction with Microsoft SQL Server databases, allowing AI assistants to list tables, read data, and execute SQL queries through a controlled interface.

Enables AI assistants to connect and query Microsoft SQL Server databases using natural language, executing read-only SQL queries for safe data inspection and analysis.

An easy-to-use bridge that lets AI assistants like Claude and Cursor IDE directly query and explore Microsoft SQL Server databases. No coding experience required!

Enables safe, read-only querying and schema exploration for Microsoft SQL Server databases with preconfigured Diamond Inventory support, multiple database management, and optional HTTP API.

Enables AI clients to interact with Microsoft SQL Server databases through natural language, translating prompts into structured queries and returning clean results for AI-powered data access.

Enables AI agents to run deterministic database intelligence tasks including natural-language-to-SQL synthesis, AST SQL auditing and optimization, schema migration diffing, SQL transpilation, index and normalization advice, PII scrubbing, fixture generation, connection-pool sizing, isolation-hazard auditing, and ORM model compilation over Streamable HTTP or stdio.

Enables natural-language querying and analysis of an e-commerce SQLite database via MCP, with read-only SQL execution, table inspection, and AI-generated answers.

Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.