MCP Agent Skills Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Agent Skills Serverlist all available skills"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Agent Skills Server
A production-ready implementation of the Model Context Protocol (MCP) server designed to equip AI agents with dynamic, persistent, and executable skills.
This server adheres to the Anthropic Agent Skills Standard, enabling seamless interoperability between LLMs (Claude, GPT-4o) and local system capabilities via a standardized SKILL.md structure.
📋 Capabilities
Progressive Disclosure: Reduces context window usage by exposing only skill metadata (
explore_skills) until full instruction sets are requested (acquire_skill).Secure Script Execution: Safely executes local scripts (Python, Node.js/Bun, Bash/PowerShell) encapsulated within skill directories.
Cross-Platform Runtime: Built on the Bun runtime for native performance on Windows, macOS, and Linux without complex environment handling.
Zero-Config Discovery: Automatically scans and registers valid skills from the
./skillsdirectory.
Related MCP server: Search MCP Server
🚀 Installation
Option A: Global Installation (Recommended for Persistence)
Install the package globally to ensure the server is always available:
npm install -g mcp-agent-skillsOption B: Run via NPX (Zero-Installation)
Execute the server on-demand without local installation:
npx mcp-agent-skillsOption C: Local Deployment (For Contributors)
Clone the repository to develop custom skills or modify core logic.
⚙️ Configuration
To use this server with your AI client, add the following configuration.
Claude Desktop
Located at:
Windows:
%APPDATA%\Claude\claude_desktop_config.jsonmacOS:
~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"agent-skills": {
"command": "npx",
"args": ["-y", "mcp-agent-skills"]
}
}
}> Dev Note: If running from source, replace command with bun and args with ["run", "/absolute/path/to/index.ts"].
Cursor IDE
Navigate to Settings > General > MCP Servers.
Click Add new MCP server.
Enter the configuration:
Name:
agent-skillsType:
commandCommand:
npx -y mcp-agent-skills
Zed Editor
Edit .config/zed/settings.json:
{
"context_servers": {
"agent-skills": {
"command": "npx",
"args": ["-y", "mcp-agent-skills"]
}
}
}🛠️ Creating Custom Skills
A Skill is a self-contained directory that teaches an agent how to perform a specific task.
Directory Structure
skills/
└── my-custom-skill/
├── SKILL.md # Definition & Instructions (Required)
├── README.md # Human-readable documentation
└── scripts/ # Executable logic
└── analyze.pyThe SKILL.md Standard
The entry point must contain YAML frontmatter followed by Markdown instructions.
---
name: Data Processor
description: Clean and normalize CSV datasets using Python.
version: 1.0.0
---
# Instructions
1. When the user provides a CSV file path, execute the cleaning script.
2. Report the number of rows processed.
## Tools
Use `run_skill_script` to execute `scripts/clean.py`.🔒 Security Implications
This MCP server grants the connected AI agent the ability to:
Read Files: Access
SKILL.mdand associated resources within the package directory.Execute Code: Run scripts defined in the
skillsfolder using local runtimes (Python, Node, Shell).
Recommendation: Only install skills from trusted sources. Review scripts/ content before loading a new skill if you are running a custom fork.
🤝 Contributing
Contributions are welcome. Please ensure your skills follow the directory structure and include a README.md.
Fork the repository.
Create a feature branch (
git checkout -b feature/new-skill).Commit your changes.
Open a Pull Request.
📄 License
This project is licensed under the MIT License.
This server cannot be installed
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