skillproof-mcp
Check whether a Claude Code skill works before installing it by querying tested verdicts and scores.
README
SkillProof MCP
Ask whether a Claude Code skill actually works — before you install it.
GitHub has tens of thousands of SKILL.md files. Almost none have been run by anyone but their author.
SkillProof installs them from their repo, triggers them, and runs them on a real
task against a no-skill baseline. This MCP server puts those verdicts in your agent's hands.
> is there a tested skill for converting markdown to Confluence?
## Confluence — DIDN'T PASS — scored below the no-skill baseline
What our test found: Ran the bundled convert_markdown_to_wiki.py on a real sample doc: it silently
turns **bold** text into wiki _italic_ (a genuine regex bug), and leaves standard GitHub-style tables
completely unconverted, despite SKILL.md listing "tables" among the elements it handles.
That is the whole point. A directory that only lists winners tells you nothing.
Tools
| Tool | What it answers |
|---|---|
find_skill |
"Is there a tested skill for X?" — ranked matches with verdict, score, test notes, install command |
check_skill |
"Someone recommended X — is it any good?" — the verdict for one skill by name, slug, or repo |
Every answer carries one of three verdicts:
- pass — installed, triggered, and beat the no-skill baseline on a real task.
- setup — works, but needs a manual step first (the notes say which).
- didn't pass — scored below the no-skill baseline: it either couldn't run, or left you worse off than not installing it.
If nothing has been tested for your job, the server says so instead of guessing. "Not tested" is a real answer.
Install
Claude Code:
claude mcp add skillproof -- npx -y skillproof-mcp
Or add it to your MCP config by hand:
{
"mcpServers": {
"skillproof": {
"command": "npx",
"args": ["-y", "skillproof-mcp"]
}
}
}
Works in any MCP client (Claude Code, Claude Desktop, Cursor, Windsurf, Zed). Node 18+. No API key, no account.
Where the data comes from
The server reads the live catalog at skillproof.dev/api/skills.json
and caches it for 15 minutes. Nothing is bundled, so verdicts are never stale. The scoring rubric —
install /5, triggering /5, output-vs-baseline /10, docs /5 — is published at
skillproof.dev/methodology.
Catalog data is CC BY 4.0: use it, cite skillproof.dev.
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。