MCP Agileday

🚀 Agileday MCP Server

A Model Context Protocol (MCP) server for Agileday that bridges Agileday's data with LLMs, enabling natural - language queries about organizational skills.

🚀 Quick Start

The Agileday MCP Server can be run in multiple ways, each with its own steps.

Option 1: Run with Claude Desktop

Add this configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "agileday": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e", "AGILEDAY_TENANT_ID=your_tenant_id",
        "-e", "AGILEDAY_API_TOKEN=your_api_token",
        "ghcr.io/eficode/mcp-agileday:latest"
      ]
    }
  }
}

Option 2: Docker

1. Clone the repository:

git clone [https://github.com/yourusername/agileday-mcp-server.git](https://github.com/yourusername/agileday-mcp-server.git)
cd agileday-mcp-server

2. Build the image:

docker build -t agileday-mcp-server .

3. Configure Claude Desktop: Add the following to your claude_desktop_config.json (usually located at ~/Library/Application Support/Claude/ on macOS or %APPDATA%\Claude\ on Windows).

{
  "mcpServers": {
    "agileday": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e", "AGILEDAY_TENANT_ID=your_tenant_id",
        "-e", "AGILEDAY_API_TOKEN=your_api_token",
        "agileday-mcp-server"
      ]
    }
  }
}

4. Restart Claude Desktop.

Option 3: Local Python

1. Clone the repository and install dependencies:

git clone [https://github.com/yourusername/agileday-mcp-server.git](https://github.com/yourusername/agileday-mcp-server.git)
cd agileday-mcp-server
pip install -r requirements.txt

2. Configure Claude Desktop: Update your claude_desktop_config.json to point to the python script:

{
  "mcpServers": {
    "agileday": {
      "command": "python3",
      "args": ["/absolute/path/to/agileday_server.py"],
      "env": {
        "AGILEDAY_TENANT_ID": "your_tenant_id",
        "AGILEDAY_API_TOKEN": "your_api_token"
      }
    }
  }
}

Option 4: Run as service

To deploy this as a standalone service (e.g., for remote access or clients that support HTTP transport), use the http transport mode.

docker run -d \
  -p 8000:8000 \
  -e AGILEDAY_TENANT_ID=your_tenant \
  -e AGILEDAY_API_TOKEN=your_token \
  ghcr.io/eficode/mcp-agileday:latest \
  --transport http

The server will be available at: Universal Endpoint: http://localhost:8000/mcp (Supports both SSE stream and POST messages) Health Check: http://localhost:8000/health

✨ Features

This server implements the following tools:

• find_experts_with_skill
  • Query: "Who knows React?"
  • Action: Searches for employees who possess a specific skill and returns their proficiency levels.
• get_employee_competence_profile
  • Query: "What are Jane Doe's top skills?"
  • Action: Retrieves a full list of skills, proficiency levels, and motivation for a specific employee.
• list_organization_skills
  • Query: "What skills do we have in the organization?"
  • Action: Retrieves the full taxonomy of skills available in your Agileday workspace, grouped by category. This helps the AI understand exactly which terms to search for and avoids guessing.

📦 Installation

You need the following environment variables to run the server:

💻 Usage Examples

Basic Usage

Once connected, you can ask Claude questions like:

• "Who are the experts in Python at our company?"
• "Find me someone who knows Service Design and has a high proficiency."
• "What is Jane Doe's competence profile?"
• "Do we have enough people with Kubernetes skills?"

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

⚠️ Important Note

• API Tokens: Never commit your AGILEDAY_API_TOKEN to version control. Always pass it via environment variables or your local config file.
• ReadOnly Access: It is recommended to use an API token with read - only permissions if possible, as this tool only fetches data.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository.
2. Create your feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the branch (git push origin feature/AmazingFeature).
5. Open a Pull Request.