mcp-alchemy: A MCP server that gives the LLM access to and knowledge about relational databases like SQLite, Postgresql

by runekaagaard · MCP Server · ★ 420

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

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. Full audit →

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.

Quick Facts

Stars420
Forks62
LanguagePython
CategoryMCP Server
LicenseMPL-2.0
Quality Score75/100
Last Updated2026-10-15
Created2024-12-26
Platformsmcp, python
Est. Tokens~15k

About mcp-alchemy

MCP Alchemy Status: Works great and is in daily use without any known bugs. Status2: I just added the package to PyPI and updated the usage instructions. Please report any issues :) Let Claude be your database expert! MCP Alchemy connects Claude Desktop directly to your databases, allowing it to: Help you explore and understand your database structure Assist in writing and validating SQL queries...

Compatible Skills

These tools work well together with mcp-alchemy for enhanced workflows:

  • investor-agent — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (54%)
  • databao-context-engine — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • slowql — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)

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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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