Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Dynamically load Claude Code skills into AI agents without copying files.
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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.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"agent-skill-loader": {
"command": "npx",
"args": [
"-y",
"agent-skill-loader"
]
}
}
}Run this in your terminal
claude mcp add agent-skill-loader -- npx -y agent-skill-loaderPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"agent-skill-loader": {
"command": "npx",
"args": [
"-y",
"agent-skill-loader"
]
}
}
}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": {
"agent-skill-loader": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"agent-skill-loader"
]
}
}
}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.
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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 back1ply, 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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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 (1.2.1) reached the registry 22 days 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, topo^alpin
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.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
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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.