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    PG-MCP is an HTTP server implementation that enables AI systems to interact with PostgreSQL databases via MCP, providing tools for querying, connecting to multiple databases, and exploring schema resources. The system enriches context by extracting table/column description from database catalogs.
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    27
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    Enables AI assistants to query PostgreSQL databases, inspect schemas, and retrieve complete DDL with built-in read-only protection. It supports multiple database connections and allows for secure database interaction and exploration via the Model Context Protocol.
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    MIT
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    A lightweight Postgres MCP server for safe database exploration and query analysis, read-only by default, with multi-database support.
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    MIT
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    A Model Context Protocol server for PostgreSQL that enables database operations like querying, schema inspection, performance analysis, and administration through a JSON-RPC 2.0 interface.
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    MIT
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    🧠 A high-performance PostgreSQL-backed MCP server acting as a super memory, task tracker, and dynamic database manager for AI agents. Features built-in connection pooling, a professional tasks schema, and a unique shared multi-agent coordination hub to prevent coding conflicts in real-time.
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    MIT
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    A Model Context Protocol server for PostgreSQL databases that enables AI agents to connect, query, and explore multiple databases with schema discovery and extension context.
    Last updated
    541
    MIT
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    Securely connect AI assistants to PostgreSQL databases with read-only access, schema discovery, querying, and performance analysis tools.
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    MIT
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    A secure vector-based memory server that provides persistent semantic memory for AI assistants using sqlite-vec and sentence-transformers. It enables semantic search and organization of coding experiences, solutions, and knowledge with features like auto-cleanup and deduplication.
    Last updated
    MIT