No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by xataio · Agent Tool · ★ 1.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent safe to install? View the security audit →
Xata Agent, your AI expert in PostgreSQL Xata Agent is an open source agent that monitors your database, finds root causes of issues, and suggests fixes and improvements. It's like having a new SRE hire in your team, one with extensive experience in Postgres. Letting the agent introduce itself: Hire me as your AI PostgreSQL expert. I can: - watch logs & metrics for potential issues. - proactively suggest configuration tuning for your database instance. - troubleshoot performance
| Stars | 1,091 |
| Forks | 82 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 61.7664635616318/100 |
| Open Issues | 51 |
| Last Updated | 2026-04-20 |
| Created | 2025-02-17 |
| Platforms | node |
| Est. Tokens | ~218k |
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agent is AI agent expert in PostgreSQL. It is categorized as a Agent Tool with 1.1k GitHub stars.
agent is primarily written in TypeScript. It covers topics such as agent, ai, anthropic.
You can find installation instructions and usage details in the agent GitHub repository at github.com/xataio/agent. The project has 1.1k stars and 82 forks, indicating an active community.
agent is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agent on Agent Skills Hub include dbhub, Unity-MCP, tools. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: