krusch-context-mcp: Persistent working memory and invariant steering MCP server for AI coding agents

by kruschdev · MCP Server · ★ 71

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

How to install krusch-context-mcp

npx krusch-context-mcp init
claude mcp add krusch-context -- npx -y krusch-context-mcp

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 66/100

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.

ai-agentsantigravityclaudeclaude-codecontext-engineeringcursorllmmcpmcp-servermodel-context-protocol

Quick Facts

Stars71
Forks6
LanguageJavaScript
CategoryMCP Server
LicenseMIT
Quality Score66/100
Last Updated2026-10-20
Created2026-05-06
Platformsclaude-code, docker, mcp, node
Est. Tokens~15k

About krusch-context-mcp

Krusch Context MCP Local MCP server: five tools to store, retrieve, and retire project decisions. SQLite by default. -lightgrey.svg) 📖 Read the Systems Deep Dive: Check out the published architecture essay Beyond Flat Vector RAG: What Makes krusch-context-mcp Special on krusch.dev, or the local companion guide in .

Compatible Skills

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

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  • brain.md — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)
  • agentlytics — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)
  • vibes-plug — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)

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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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