skills: Firecrawl agent skills for Claude Code, Codex and Cursor

by firecrawl · MCP Server · ★ 145

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

How to install skills

npx skills add firecrawl/skills
npx skills add firecrawl/skills --skill firecrawl-build

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 70/100

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.

agent-skillsclaude-code-skillsfirecrawlmcpweb-scrapingweb-search

Quick Facts

Stars145
Forks36
CategoryMCP Server
LicenseISC
Quality Score70/100
Open Issues5
Last Updated2026-11-04
Created2026-04-08
Platformsbrowser, claude-code, codex, mcp
Est. Tokens~17k

About skills

Firecrawl Skills The full catalog of Firecrawl skills for AI coding agents, following the Agent Skills format. Available as a plugin for Claude Code, Cursor, and OpenAI Codex. This repository is a distribution catalog. Every directory under is a CI-synced mirror. Install skills from here; contribute skill changes at the source repository. Repository-level metadata is maintained here.

Compatible Skills

These tools work well together with skills for enhanced workflows:

  • llm-reader — semantic(0.42)+complementary+shared_fw(openai)+rare_topics+similar_pop+shared_platform (67%)
  • Web-Use — semantic(0.30)+complementary+shared_fw(openai)+similar_pop+shared_platform (59%)

skills alternative? Top 6 similar tools

Looking for a skills alternative? If you're comparing skills with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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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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