PostgreSQL向けに構築された126個のMCPを発見。
Integrates vector similarity search and storage directly into PostgreSQL.
Provides a high-performance database client library for Python's asyncio framework to interact with PostgreSQL.
Empowers AI coding tools to generate robust, performant, and modern PostgreSQL code by providing deep, versioned expertise.
Provides scalable, fast, and disk-friendly vector search capabilities directly within PostgreSQL.
Exposes PostgreSQL databases to AI agents via the Model Context Protocol, offering rich schema discovery and query capabilities.
Enables AI assistants to safely query any PostgreSQL database using natural language, returning structured SQL results.
Provides PostgreSQL database management capabilities, assisting with analysis, debugging, schema management, data migration, and monitoring.
Connects Large Language Models to PostgreSQL databases, enabling controlled querying and analysis.
Provides professional, read-only operations and monitoring for PostgreSQL databases, offering performance insights, structure visibility, and configuration details.
Enables natural language agents and clients to perform SQL queries and interact with PostgreSQL databases securely in a read-only fashion.
Extends PostgreSQL with advanced vector search, machine learning algorithms, and agent runtime capabilities.
Enables AI agents to interact with PostgreSQL databases through a standardized Model Context Protocol (MCP).
Provides HTTP and Stdio transports for interacting with PostgreSQL databases through the Model Context Protocol.
Extends a PostgreSQL MCP server with functionalities to create, read, update, and delete database tables and entries, facilitating LLM interaction with databases.
Enables AI agents to discover, connect to, query, and understand PostgreSQL databases using the Model Context Protocol.
Empower Large Language Models with full read-write access to PostgreSQL databases, enabling both querying and modification of content with robust safety controls.
Provides PostgreSQL database management capabilities, assisting with analysis, guidance, and debugging.
Optimize PostgreSQL database performance with AI-powered query analysis, index recommendations, and health monitoring.
Exposes relational databases to AI agents, enabling natural language queries and structured result retrieval.
Enables AI agents to interact with PostgreSQL databases through a standardized Model Context Protocol (MCP) interface.
Scroll for more results...