About Agent Skill Loader
Agent Skill Loader is an MCP server that makes Claude Code Skills available to AI agents through prompts and tools. It discovers skills in configured directories and notifies clients when files change.
Key features
- 01Expose skills as MCP prompts
- 02Discover and search skill directories
- 03Read SKILL.md instructions
- 04Install skills in a project
- 05Watch for skill changes
Use cases
- 01Invoke a skill as a client slash command
- 02Let an agent find and read relevant instructions
- 03Add or remove skill search paths at runtime
MCP support
Exposes discovered skills as MCP Prompts and tools for listing, reading, installing, and managing search paths. File changes trigger listChanged notifications.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
5Saved tool list · updated 2w ago
This tool takes no parameters.
Details
From the project READMEAgent Skill Loader 🧠
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.
🚀 Features
- MCP Prompts: Skills appear as slash commands in clients. No tool call needed to inject them.
- Live updates:
listChangednotification fires when skills are added or removed (via file watcher). - Discovery:
list_skills— scans configured skill directories, with optional search filter. - Dynamic Learning:
read_skill— fetches theSKILL.mdcontent. - Persistence:
install_skill— copies a skill permanently to your project. - Configuration:
manage_search_paths— add/remove skill directories at runtime. - Troubleshooting:
debug_info— diagnose configuration and path issues.
🛠️ Setup
Prerequisites
- Node.js >= 18
Option A: Install from npm (Recommended)
npm install -g agent-skill-loader
Then register in .mcp.json:
"agent-skill-loader": {
"command": "agent-skill-loader"
}
Option B: Build from Source
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": ["<path-to-repo>/build/index.js"]
}
📂 Configuration
The server automatically detects its workspace and aggregates skill paths from:
- Default:
%USERPROFILE%\.claude\plugins\cache(Standard location) - Dynamic Config:
skill-paths.json(Located in the project root)
Environment Variables
| 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) |
Dynamic Path Management
You do not need to manually edit config files. Use the tool to manage paths at runtime:
- Add:
manage_search_paths(operation="add", path="F:\\My\\Deep\\Skills") - Remove:
manage_search_paths(operation="remove", path="...") - List:
manage_search_paths(operation="list")creates/updatesskill-paths.json.
🤖 Usage
MCP Prompts (Slash Commands)
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.
Tools
The agent has access to five tools:
list_skills(query?): Returns a JSON list of available skills. Optionalqueryfilters 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/<name>. For security,target_pathmust 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).
Example Agent Prompt
"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.
🔧 Troubleshooting
If skills aren't being discovered, use debug_info() to see:
- search_paths: Which directories are being scanned
- path_status: Whether each path exists and is readable
- warnings: Any errors encountered during scanning (permission denied, empty files, etc.)
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" }
]
}
📦 Project Structure
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).
🤝 Contributing
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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.