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Basic Information

Xata Agent is an open source AI agent designed to act as a PostgreSQL expert for SREs and DBAs. It monitors databases, inspects logs and metrics, diagnoses root causes of operational issues, and suggests non-destructive fixes and configuration tuning. The agent runs self-hosted using provided Docker images and a Postgres instance for storing configuration, state, and history. It uses preset SQL statements and troubleshooting queries against PostgreSQL internals such as query statistics and locks. The project is extensible and intended to be run alongside existing cloud databases including AWS RDS, Aurora, and Google Cloud SQL. The README emphasizes safe operation by avoiding destructive commands, integration options like Slack notifications and OAuth for authentication, and support for multiple LLM providers for reasoning and recommendations.

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App Details

Features
The repository provides a self-hostable agent packaged as Docker images with a docker-compose example and a web app reachable at a configured PUBLIC_URL. It includes TypeScript "tools" that the agent can call to inspect databases, human-readable playbooks that encode troubleshooting workflows, and integrations for AWS (CloudWatch for RDS/Aurora) and Slack. The agent uses preset SQL queries to probe PostgreSQL internals such as pg_stat_statements and pg_locks, supports multiple LLM models (OpenAI, Anthropic, Deepseek), and stores state and history in a Postgres database. The project includes a demo, development instructions for the apps/dbagent subdirectory, CI badges, a roadmap of supported playbooks and cloud providers, and plans for a cloud-hosted offering and additional integrations.
Use Cases
Xata Agent automates routine database observability and first-line troubleshooting so teams can detect and resolve performance and operational issues more quickly. It reduces manual investigation by watching logs and metrics, proposing tuning and indexing suggestions, and running curated, non-destructive diagnostic queries. Teams can receive alerts and recommendations via Slack, extend the agent with custom TypeScript tools and playbooks, and adapt monitoring to RDS, Aurora and Google Cloud SQL. The self-hosted model lets organizations control data and store agent state locally, while the roadmap and extensibility support adding custom checks, integrations, and evaluation of agent-LLM interactions. The project is used internally at Xata and includes deployment guidance and an onboarding UI for operators.

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