找到适合你的 MCP Server，快速完成接入

A multi-functional computing platform server designed to integrate with large language models like Qwen, providing file access, database connections, API integration, and vector database functionality.

Provides access to MySQL databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly, readwrite, full) and table-level permissions using whitelists, blacklists, wildcards, and regex patterns.

Enables secure access to Oracle databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly/readwrite/full) and table-level permissions for safe query execution and data management.

Manages agent certification by tracking trust scores, capabilities, and test results via a PostgreSQL database. It allows users to verify agent skills, report test outcomes, and automatically certify agents based on performance thresholds.

An extensible MCP server that integrates Odoo with LLMs to enable querying and managing business data like partners, quotations, and sales orders. It supports custom tool registration and multiple transport protocols for both local and remote communication.

A proof-of-concept MCP server demonstrating various capabilities including mathematical calculations, URL fetching, system information retrieval, data processing, and file operations.

A Snowflake MCP server — SQL queries, schema exploration, and data insights for AI assistants

Enables Claude to function as a full-stack software engineer with comprehensive development capabilities including project creation, database management, frontend/backend development, testing, deployment, and DevOps operations across multiple frameworks and technologies.

Provides comprehensive control over Google Sheets to read, write, format, and manage spreadsheets directly through natural language. It includes extensive tools for data manipulation, conditional formatting, and cell protection, along with integrated PostgreSQL database query capabilities.

An AI-powered SQLite assistant that converts natural language to SQL queries with full schema awareness, enabling users to interact with databases using conversational language.

Enables natural language database querying through GPT-powered SQL generation and execution with metadata-driven validation and intermediate representation.

A server that exposes SQLite database operations as tools, allowing natural language interactions with a database through LlamaIndex and Ollama LLM integration.

Analyzes SQL queries for performance issues, provides optimization suggestions with automated rewriting, and recommends indexes across multiple database dialects (PostgreSQL, MySQL, Oracle, SQL Server).

An MCP server for Microsoft SQL Server that enables executing read-only queries, listing tables, and describing database schemas. It offers specialized support for custom ports and multiple authentication methods including SQL credentials, NTLM, and Windows Integrated Auth.

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.

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.

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.

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.

A Python utility for adding usage tracking, analytics, and audit trails to MCP servers using SQLite-backed persistence. It enables developers to monitor tool, prompt, and resource activity and expose these statistics directly to LLM clients.

Generates tailored system architecture recommendations based on business parameters like QPS, concurrent users, database type, and AI model size, providing resource allocation plans, middleware suggestions, and exportable architecture diagrams.