GrapeRoot: Compounding Context for AI Coding Assistants — MCP graph engine for Claude Code, Cursor, Copilot, Gemini

by kunal12203 · MCP Server · ★ 1.0k

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

Security audit verdict: SAFE · quality 74/100

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-codingclaude-codecontext-enginecopilotcursorgeminigraperootmcp

Quick Facts

Stars1,045
Forks121
LanguagePowerShell
CategoryMCP Server
LicenseApache-2.0
Quality Score74/100
Open Issues23
Last Updated2026-09-03
Created2026-02-21
Platformsclaude-code, gemini, mcp
Est. Tokens~19k

About GrapeRoot

    Compounding Context for AI Coding Assistants Website · Docs · Benchmarks · Discord 🌐 Read this in your language: English · 中文 · Español · हिंदी · Français · Deutsch ·

Compatible Skills

These tools work well together with GrapeRoot for enhanced workflows:

  • cli-continues — semantic(0.34)+complementary+similar_pop+shared_platform (52%)
  • harmonyos-ai-skill — semantic(0.34)+complementary+similar_pop+shared_platform (52%)
  • agtx — semantic(0.32)+complementary+similar_pop+shared_platform (51%)
  • ai-coding-guide — semantic(0.30)+complementary+similar_pop+shared_platform (50%)
  • snip — semantic(0.28)+complementary+similar_pop+shared_platform (50%)

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  • postman-mcp-server by postmanlabs · ⭐ 325

    Postman MCP Server — connect AI agents (Claude Code, Cursor, VS Code Copilot, Gemini CLI) to your Postman coll

  • SocratiCode by giancarloerra · ⭐ 3.4k

    Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP:

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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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