Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Expose local Agent Skills as adapter tools, MCP resources, MCP tools, and share artifacts.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
SKILL_DECK_SKILLS_ROOTYou need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"skill-deck": {
"command": "npx",
"args": [
"-y",
"skill-deck"
],
"env": {
"SKILL_DECK_SKILLS_ROOT": "your-value"
}
}
}
}Run this in your terminal
claude mcp add skill-deck --env SKILL_DECK_SKILLS_ROOT=your-value -- npx -y skill-deckFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"skill-deck": {
"command": "npx",
"args": [
"-y",
"skill-deck"
],
"env": {
"SKILL_DECK_SKILLS_ROOT": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"skill-deck": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"skill-deck"
],
"env": {
"SKILL_DECK_SKILLS_ROOT": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account xingbofeng, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: SKILL_DECK_SKILLS_ROOT
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 6 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, HotCodePush
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
中文 · English · 官网 · 快速开始 · GitHub
把散落在本机的 Agent Skills,变成模型看得见、用得上、也分享得出去的能力牌组。
Adapter for runtimes, MCP dynamic discovery, and share artifacts generated through agent conversation.
SkillDeck 是本地 Agent Skill 的适配、激活与分享工具。
它解决三个很具体的场景:
| 场景 | 为什么需要它 | SkillDeck 做什么 |
|---|---|---|
| 我有一组 Skill,想通过工具的方式接入 OpenAI Agent SDK。 | OpenAI 已把 SKILL.md 定义成可复用工作流,Agents SDK 也支持 local skills,但手写 schema、handler 和 stable id 很繁琐。 | Adapter 扫描、解析、校验 SKILL.md,生成 provider-neutral tools 和 runtime handlers,让同一套 Skills 可以接入不同 Agent runtime。 |
| 我有一组 Skill,想接到 Claude Code、Cursor 或其他 MCP host。 | 只给 list_skills / read_skill 不够,模型不一定知道复杂任务要先查本地 Skills。 | MCP + Skill Activation 把 Skills 暴露成 tools/resources,并通过 compact / guided / active 三种模式,让模型在任务里自己发现、搜索和加载 Skill。 |
| 我有一组 Skill,想发给同事、同行或社交平台看。 | 私有 Skill 往往含本地路径、secret、私有 URL;只发截图又无法搜索、下钻和复用。 | Share 通过 MCP 让 agent 生成完整分享页和双图,默认脱敏,可搜索、可下钻、可审阅再接入。 |
背景参考:OpenAI Skills guide、Skills in ChatGPT、Agents SDK tools、openai-agents-python #2906。
对应到产品能力,它做三件事:
| 主线 | 作用 | 结果 |
|---|---|---|
| Adapter | 扫描、解析、校验本地 SKILL.md,生成 stable id、provider-neutral tools 和 runtime handlers。 | 同一套 Skills 可接 OpenAI、Anthropic、OpenAI Agents SDK、本地 runtime。 |
| MCP | 把 Skills 暴露成 MCP tools/resources,并通过 Skill Activation 帮模型动态发现。 | 模型可以通过 skill_guide、use_skill_*、search_skills、read_skill 加载 Skill。 |
| Share | 你和 agent 说“帮我分享这套 Skills”,agent 通过 MCP 生成静态分享页和双图,默认脱敏。 | 适合朋友圈、小红书和同行交流,不暴露本地路径、secret 和私有 URL。 |
它不是公开 marketplace,也不是远程托管服务。用户的 Skill 目录仍然在本机。
默认的 list_skills / read_skill 能读 Skill,但模型不一定会主动调用。SkillDeck 增加三种模式,让模型更容易发现并加载本地 Skill。
| 模式 | 暴露内容 | 模型怎么发现 Skill | 适合场景 | 代价 |
|---|---|---|---|---|
compact | list_skills、search_skills、get_skill_info、read_skill、resources | 模型需要主动搜索或列目录 | 兼容旧行为、Skill 很多、工具列表要短 | 自动发现能力弱 |
guided | compact + skill_guide + MCP instructions | 模型看到 skill_guide 后获得使用指南 | 想提高发现概率,但不想每个 Skill 都变 tool | 仍依赖模型调用向导 |
active | guided + 最多 N 个 use_skill_ _ | 模型在 tools/list 阶段直接看到常用 Skill | 想最大化自动发现效果 | 工具数量增加 |
示例:
npx -y skill-deck mcp serve \
--skills ~/.skills
安装:
npm install skill-deck
第一步,选择一种 Skill Activation 模式安装 MCP。推荐先用默认 active:
三种命令的 MCP server 名都叫 skill-deck;切换模式时更新同名 server 即可。
# active:默认模式,常用 Skill 会直接出现在 tools/list
claude mcp add skill-deck \ -- npx -y skill-deck mcp serve \ --skills ~/.codex/skills
# guided:暴露 skill_guide,让模型先看分组和推荐入口
claude mcp add skill-deck \ -- npx -y skill-deck mcp serve \ --skills ~/.codex/skills \ --skill-mode guided
# compact:只暴露 list/search/info/read/resources,工具列表最短
claude mcp add skill-deck \ -- npx -y skill-deck mcp serve \ --skills ~/.codex/skills \ --skill-mode compact
Codex / 其他 MCP host 使用同一组 stdio 参数;如需切换模式,在 args 中追加 --skill-mode 和对应值:
{
"mcpServers": { "skill-deck": { "command": "npx", "args": [ "-y", "skill-deck", "mcp", "serve", "--skills", "~/.codex/skills" ] } } }
第二步,在 Claude / Codex 中确认 skill-deck 已连接。Claude Code 里输入:
/mcp
第三步,直接对 agent 说:
请使用 SkillDeck MCP 的 generate_skill_share 工具,为当前已加载的 ~/.codex/skills 生成一套可以分享给同行看的 Skill 工作流分享物。
需要指定输出目录时,再追加:
输出到 ~/skilldeck-shares/codex-skills-share,注意脱敏,并在完成后告诉我 index.html、cover.png、detail.png 和 manifest.json 的路径。
分享不是让你手写配置,也不是把私有 Skill 扔到公开市场。你只需要和 agent 对话:
帮我把 ~/.skills 这套 Skills 做成一个可以发给同行看的分享页和两张分享图,注意脱敏。
agent 会通过 SkillDeck 的 MCP Share 接口生成:
share/
index.html cover.png detail.png
index.html 是完整介绍页,支持搜索和下钻到 Skill 详情;cover.png 适合传播,detail.png 适合给同行看技术细节。默认会移除本地路径、secret 和私有 URL,reference 只展示路径,不读取文件内容。
实际生成效果:
compact / guided / active。skill_guide 和 use_skill_*。skill-deck。server.json + npm/stdio 元数据。更完整的在线文档见 skill.counterxing.top。
MIT