PostgreSQL FAQs

Question 1

How many tools are included and how does tool filtering work?

Accepted Answer

The server includes 106 specialized tools across 12 categories. Tool filtering allows users to selectively expose specific tools or groups to AI assistants, which is crucial for staying within AI IDE tool limits and managing context effectively.

Question 2

Does PostgreSQL MCP support advanced PostgreSQL features and extensions?

Accepted Answer

Yes, it offers robust support for native JSONB operations, full-text search, and includes dedicated tools for popular extensions like `pgvector` for AI/ML vector similarity search and `PostGIS` for complex geospatial queries and spatial indexing.

Question 3

What are the core capabilities and enterprise-grade features?

Accepted Answer

Core capabilities include full SQL support, JSONB operations, efficient connection pooling, and performance tools. Enterprise features, coming soon, include secure OAuth 2.0 authentication (RFC 9728/8414 compliant), advanced tool filtering for granular control, and comprehensive monitoring capabilities.

Question 4

What is PostgreSQL MCP and how does it benefit AI assistants?

Accepted Answer

PostgreSQL MCP (Model Context Protocol) Server enables AI assistants like Claude and Cursor to securely interact with PostgreSQL databases. It provides a structured way for AI to perform administration, observability, and querying tasks using a suite of specialized tools.

Question 5

What kind of database operations can AI assistants perform with PostgreSQL MCP?

Accepted Answer

AI assistants can execute a wide range of database operations including Core CRUD, transaction management, JSONB manipulation, full-text search, performance analysis (EXPLAIN ANALYZE), schema design, and specialized tasks leveraging pgvector (AI vector search) and PostGIS (geospatial operations) extensions.

PostgreSQL

PostgreSQL

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Key Features

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About

Key Features

Use Cases