Installation can be done via Docker or manually, requiring Python 3.13+ and PostgreSQL databases. The server supports testing scripts for verifying functionality and includes tools for AI agents to interact with the database. Built on the Model Context Protocol, FastMCP, asyncpg, and YAML, the server operates in read-only mode by default for security, with connection details protected through opaque connection IDs. Contributions are encouraged, particularly in expanding extension context files and schema introspection resources.
Key takeaways:
- PG-MCP is a comprehensive server implementation of the Model Context Protocol for PostgreSQL, offering enhanced capabilities for AI agents to interact with databases.
- Key features include multi-database support, rich catalog information, extension context, and robust connection management.
- The server supports connection management, query tools, schema discovery, and data access resources, with built-in support for PostgreSQL extensions like PostGIS and pgvector.
- Installation can be done via Docker or manually, and the server is designed with security considerations, running in read-only mode by default.