Battle-tested in PostgresAI team's work with companies like GitLab, Miro, Chewy, Suno, Supabase, Gadget, and more — now packaged for easy use by humans and AI agents.
Why postgresai?
Traditional monitoring tools give you dashboards. postgresai gives AI agents the context they need to actually fix problems.
- Structured for AI — Reports and metrics designed for LLM consumption
- Issues workflow — Track problems from detection to resolution
- 45+ health checks — Bloat, indexes, queries, settings, security
- Active Session History — Postgres's answer to Oracle ASH
- Expert dashboards — Four Golden Signals methodology
Part of Self-Driving Postgres — PostgresAI's open-source initiative to make Postgres autonomous.
Get Started
1. Sign up
Create a free account at postgres.ai
2. Authenticate
npx postgresai auth
This opens your browser to log in and saves your API key locally.
3. Run health checks
PGPASSWORD=secret npx postgresai checkup postgresql://user@host:5432/dbname
4. View results
Open console.postgres.ai to see:
- Detailed reports with suggested fixes
- Issues workflow to track remediation
- Historical data across all your projects
Offline mode: Add --no-upload to run locally without an account.
See demo
Express Checkup
Run specific checks or work offline:
# Run a specific check
npx postgresai checkup --check-id H002 postgresql://...
# Local JSON output only (no upload)
npx postgresai checkup --no-upload --check-id H002 postgresql://...
Tips: npx pgai checkup also works. bunx postgresai if you prefer Bun.
Full monitoring stack
For continuous monitoring with dashboards, install the full stack on a Linux machine with Docker:
# Quick demo with sample data
npx postgresai mon local-install --demo
# → Open http://localhost:3000
# Production setup (Linux + Docker required)
npx postgresai prepare-db postgresql://admin@host:5432/dbname # Create monitoring role with minimal permissions
npx postgresai mon local-install --api-key=YOUR_TOKEN --db-url="postgresql://..."
Get your API key at console.postgres.ai — or use the fully managed version there.
Production-safe
All diagnostic queries are carefully designed to avoid the observer effect — they use timeouts, row limits, and non-blocking approaches. Battle-tested on production databases with dozens of TiB of data, hundreds of kTPS, and millions of DB objects.
Preview the setup SQL before running:
npx postgresai prepare-db --print-sql postgresql://... # Review what will be created
The prepare-db step creates a read-only postgres_ai_mon user with minimal permissions, enables pg_stat_statements, and creates postgres_ai schema with a few helper views.
What's inside
