cve-intel: Local security intelligence for CVE triage - 39 data sources and 36 tools, risk scores and an MCP server

by Fazmin · MCP Server · ★ 91

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

How to install cve-intel

claude mcp add cve-intel -- "/Applications/CVE Intel.app/Contents/MacOS/cve-intel" mcp
docker run --rm -p 127.0.0.1:8000:8000 --env-file .env cve-intel

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

Security audit verdict: SAFE · quality 65/100

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.

artificial-intelligencecve-searchcybercybersecuritycybersecurity-educationcybersecurity-toolslocal-firstprivacyvulnaribility

Quick Facts

Stars91
Forks5
LanguageRust
CategoryMCP Server
LicenseApache-2.0
Quality Score65/100
Open Issues1
Last Updated2026-10-23
Created2026-10-18
Platformsmcp, rust
Est. Tokens~28k

About cve-intel

🛡️ CVE Intel Local security intelligence in native Rust — a Tauri desktop app, a one-click built-in small AI model (llama.cpp), an MCP server for any harness, a REST API, and a plain CLI. 31 tools, 25 data sources. Private on-device AI by default; OpenAI, Anthropic or Gemini are an opt-in setting.

Compatible Skills

These tools work well together with cve-intel for enhanced workflows:

  • deadend-cli — semantic(0.22)+complementary+shared_fw(anthropic,openai)+rare_topics+similar_pop (63%)
  • deadend-cli — semantic(0.22)+complementary+shared_fw(anthropic,openai)+rare_topics+similar_pop (63%)

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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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