Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Dynamically load Claude Code skills into AI agents without copying files.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"agent-skill-loader": {
"command": "npx",
"args": [
"-y",
"agent-skill-loader"
]
}
}
}在终端中运行这条命令
claude mcp add agent-skill-loader -- npx -y agent-skill-loader粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agent-skill-loader": {
"command": "npx",
"args": [
"-y",
"agent-skill-loader"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"agent-skill-loader": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"agent-skill-loader"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 back1ply 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.2.1)于22天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Toggl 2.0
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Toggl 2.0 MCP server for tasks, projects, time entries, and workspace operations.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Agent Skill Loader is a Model Context Protocol (MCP) server that acts as a bridge between your static Claude Code Skills library and dynamic AI agents (like Claude Desktop, Cursor, or any MCP client).
It exposes skills both as MCP Prompts (slash commands, zero tool calls needed) and as MCP Tools (for programmatic use). Skills are auto-discovered from configured directories and stay live — add a new SKILL.md and the client is notified automatically.
listChanged notification fires when skills are added or removed (via file watcher).list_skills — scans configured skill directories, with optional search filter.read_skill — fetches the SKILL.md content.install_skill — copies a skill permanently to your project.manage_search_paths — add/remove skill directories at runtime.debug_info — diagnose configuration and path issues.npm install -g agent-skill-loader
Then register in .mcp.json:
"agent-skill-loader": {
"command": "agent-skill-loader" }
git clone https://github.com/back1ply/agent-skill-loader.git
cd agent-skill-loader npm install npm run build
Then register in .mcp.json:
"agent-skill-loader": {
"command": "node", "args": [" /build/index.js"] }
The server automatically detects its workspace and aggregates skill paths from:
%USERPROFILE%\.claude\plugins\cache (Standard location)skill-paths.json (Located in the project root)| Variable | Description |
|---|---|
MCP_SKILL_PATHS | JSON array or semicolon/comma-separated list of additional skill paths |
MCP_WORKSPACE_ROOT | Override auto-detected workspace root |
MCP_NO_WATCH | Set to 1 to disable the file watcher (useful in CI) |
You do not need to manually edit config files. Use the tool to manage paths at runtime:
manage_search_paths(operation="add", path="F:\\My\\Deep\\Skills")manage_search_paths(operation="remove", path="...")manage_search_paths(operation="list") creates/updates skill-paths.json.If your client supports MCP Prompts (Claude Desktop, Cursor, etc.), skills appear automatically as slash commands. Select a skill from the slash command menu to inject its content directly — no tool calls needed.
The agent has access to five tools:
list_skills(query?): Returns a JSON list of available skills. Optional query filters by name/description substring (case-insensitive).read_skill(skill_name): Returns the markdown instructions for a skill.install_skill(skill_name, target_path?): Copies the skill folder to .agent/skills/ . For security, target_path must be within the current workspace.manage_search_paths(operation, path?): Add, remove, or list skill search paths.debug_info(): Returns diagnostic information (paths, status, warnings)."I need to write a DAX measure but I'm not sure about the best practices."
The agent will automatically call list_skills, find writing-dax-measures, call read_skill, and answer with expert knowledge. Or the user can invoke the skill directly as a slash command.
If skills aren't being discovered, use debug_info() to see:
Example output:
{
"workspace_root": "C:/projects/agent-skill-loader", "search_paths": { "base": ["C:/Users/pc/.claude/plugins/cache"], "dynamic": ["F:/My/Skills"], "effective": ["C:/Users/pc/.claude/plugins/cache", "F:/My/Skills"] }, "path_status": [ { "path": "C:/Users/pc/.claude/plugins/cache", "exists": true, "readable": true }, { "path": "F:/My/Skills", "exists": false, "readable": false } ], "skills_found": 12, "warnings": [ { "path": "F:/My/Skills", "reason": "Directory does not exist" } ] }
src/index.ts: Main server logic (tools + prompts + watcher).src/utils.ts: Skill scanning, description extraction, prompt helpers, debounce.build/: Compiled JavaScript output.package.json: Dependencies (@modelcontextprotocol/sdk, chokidar, zod).To add new skills, add a folder with a SKILL.md file to one of the watched directories. The server picks them up automatically and sends a listChanged notification — no restart required.