MCP-PostgreSQL-Ops: Give AI assistants full PostgreSQL DBA superpowers — 30+ tools for performance analysis, bloat detection, lock

by call518 · MCP Server · ★ 164

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Featured in: MCP Database Tools

How to install MCP-PostgreSQL-Ops

git clone https://github.com/call518/MCP-PostgreSQL-Ops.git
pip install mcp-postgresql-ops

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 75/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentagentic-aiaiclaudedatabasedatabase-toolsdbafastmcpllmmanagement

Quick Facts

Stars164
Forks27
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score75/100
Last Updated2026-11-02
Created2025-08-19
Platformsbrowser, claude-code, mcp, python
Est. Tokens~25k

About MCP-PostgreSQL-Ops

MCP Server for PostgreSQL Operations and Monitoring Architecture & Internal (DeepWiki) Overview MCP-PostgreSQL-Ops is a professional MCP server for PostgreSQL database operations, monitoring, and management. Supports PostgreSQL

Compatible Skills

These tools work well together with MCP-PostgreSQL-Ops for enhanced workflows:

  • slowql — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (63%)
  • llmtop — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (50%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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