skillhub-mcp

skillhub-mcp

An MCP server that lets AI agents search, view, install, and validate skills from the skillhub registry through tool calls.

Category
访问服务器

README

skillhub

Trusted skill marketplace for AI agents. One manifest, many runtimes.

A skill is a small tool that an AI agent (Hermes, Claude Code, Codex, Cursor) can call as a black box. skillhub is the place where:

  • maintainers publish skills once, in a universal skill.yaml,
  • agents and humans discover them via skillhub search,
  • they install into the right runtime with skillhub install <name> <runtime>.

No domain. No accounts. No money involved — yet. Just the protocol, the CLI, and a registry of 20 seed skills.

Status

v0.0.1 — local CLI, no network, no payments. The goal of v0.0.1 is to prove the manifest format and the discoverability workflow before we add infrastructure.

What's here

File What it is
manifest_spec.md Universal skill manifest, v0.1
src/skillhub/cli.py CLI: search, show, install, validate, publish
src/skillhub_mcp/server.py MCP server exposing the same 4 tools to agents
src/skillhub/trust.py Trust Score v0.2 (real GitHub signals)
src/skillhub/scan.py Static security scanner
registry/skills.jsonl 254 curated skills (incl. skillhub-mcp itself)
registry/trust.json Cached trust scores (TTL 6h)
scripts/seed_from_sources.py Idempotent importer from public registries
scripts/enrich_tags.py Tag enrichment via token frequency
pyproject.toml uv tool install -e .

Install (local)

Requires uv (a fast Python package manager). On macOS: brew install uv. The CLI is then globally available as skillhub.

git clone https://github.com/djmarat/skillhub
cd skillhub
uv tool install -e .            # installs skillhub + skillhub-mcp
skillhub search "pdf"           # try it

To re-install after pulling new code:

cd skillhub
uv tool install -e . --force

Usage

# Search the local registry
skillhub search "search"             # human table
skillhub search "pdf" --json         # agent-friendly, one JSON per line

# Show one skill in detail
skillhub show pdf-md

# Install into a runtime
skillhub install pdf-md --runtime hermes
# or
skillhub install pdf-md -r claude-code

# Validate your own skill.yaml
skillhub validate ./my-skill/skill.yaml

As an MCP server (skillhub-mcp)

For AI agents that speak MCP (Claude Code, Hermes, Codex, Cursor), skillhub ships its own marketplace as a server. Connect once, then search/show/install/validate skills as tool calls — no copy-paste, no scraping.

{
  "mcpServers": {
    "skillhub": {
      "command": "skillhub-mcp"
    }
  }
}

If you don't have uv tool installed globally, fall back to the dev form:

{
  "mcpServers": {
    "skillhub": {
      "command": "python",
      "args": ["-m", "skillhub_mcp.server"],
      "cwd": "/path/to/skillhub"
    }
  }
}

The server exposes 15 tools — full agent lifecycle:

Tool When the agent uses it
search "I need a tool that does X"
show "Tell me more about this one"
stats "What's the community success rate? Latency?"
probe "Try a dry-run install first, don't touch my runtime"
install "Make it real"
update "Refresh me on the latest version"
uninstall "I don't need this anymore"
validate "Is this skill.yaml well-formed and safe to ship?"
rate "Did this skill work? Tell others"
recommend "What else usually goes with the stuff I have?"
profile "What have I already installed/rated in this account?"
collections "List curated bundles (AI Researcher, PDF, …)"
collection "Show one bundle details"
bundle_install "Install an entire bundle"
bundle_suggest "What bundle fits my installed skills?"

The retention loop is built in: every install writes to a local profile; every successful run is recorded as a rate; the next stats call surfaces those signals back. So agents get more confident about skills over time — not less.

See src/skillhub_mcp/server.py for the full schema.

  • Maintainers write skill.yaml once; the CLI compiles to runtime layouts.
  • Agents find skills via skillhub search --json instead of web scraping.
  • Humans get a trust_score per skill — derived from real signals, not stars.
  • Everyone agrees on the same skill.yaml schema, so we don't fork five copies of the same SKILL.md across runtimes.

Roadmap (no dates)

  • v0.1: schema stable, security scanner v1, real registry updater.
  • v0.2: trust score from install_success_rate (live telemetry).
  • v0.3: in-agent MCP-server (skillhub-mcp) so any MCP-capable agent can discover/install skills via tool calls.
  • v1.0: featured/verified tiers, paid placements, the actual marketplace.

License

MIT. See headers in source files.

推荐服务器

Baidu Map

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。

官方
精选
JavaScript
Playwright MCP Server

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。

官方
精选
TypeScript
Magic Component Platform (MCP)

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。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

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。

官方
精选
本地
TypeScript
VeyraX

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。

官方
精选
本地
graphlit-mcp-server

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。

官方
精选
TypeScript
Kagi MCP Server

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。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

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。

官方
精选