Keboola MCP Server

A Model Context Protocol (MCP) server that reveals skills exposed by the Keboola Skill Registry. This allows Claude to access and use tools from Keboola's Skill Registry directly within your conversations.

Requirements

• Keboola Skill Registry API Token (Skill Group)

Installation

PyPI Installation (Recommended)

You can install the package directly from PyPI:

pip install keboola.skill_registry_mcp

Manual Installation

First, clone the repository and create a virtual environment:

git clone https://github.com/keboola/keboola-mcp-server.git
cd keboola-mcp-server
python3 -m venv .venv
source .venv/bin/activate

Install the package in development mode:

pip3 install -e .

For development dependencies:

pip3 install -e ".[dev]"

Claude Desktop Setup

To use this server with Claude Desktop, follow these steps:

1. Create or edit the Claude Desktop configuration file:

   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json

2. Add one of the following configurations based on your installation method:

Configuration Option 1: Using Direct Python Module (Most Reliable)

{
  "mcpServers": {
    "skill_registry": {
      "command": "/path/to/your/python",
      "args": [
        "-m",
        "keboola.skill_registry_mcp",
        "--transport",
        "stdio",
        "--log-level",
        "DEBUG",
        "--api-url",
        "https://ksr.canary-orion.keboola.dev/api"
      ],
      "env": {
        "SKILL_REGISTRY_TOKEN": "SKILL_GROUP_TOKEN_FROM_REGISTRY_SERVICE"
      }
    }
  }
}

Replace /path/to/your/python with the full path to your Python executable. You can find this by running:

• On macOS/Linux: which python3 or which python
• On Windows: where python

If you installed the package in a virtual environment, make sure to use the Python path from within that environment (e.g., /path/to/your/.venv/bin/python).

Configuration Option 2: Using Command (If Available in PATH)

{
  "mcpServers": {
    "skill_registry": {
      "command": "keboola-sr-mcp",
      "args": [
        "--transport",
        "stdio",
        "--log-level",
        "DEBUG",
        "--api-url",
        "https://ksr.canary-orion.keboola.dev/api"
      ],
      "env": {
        "SKILL_REGISTRY_TOKEN": "SKILL_GROUP_TOKEN_FROM_REGISTRY_SERVICE"
      }
    }
  }
}

⚠️ Note: This option requires that the executable is properly installed and available in your system PATH. If you encounter "ENOENT" errors, use Option 1 instead.

Configuration Option 3: Using Manual Installation with Virtual Environment

{
  "mcpServers": {
   "skill_registry": {
      "command": "/path/to/keboola-skill-registry-mcp-server/.venv/bin/python",
      "args": [
        "-m",
        "keboola.skill_registry_mcp",
        "--transport",
        "stdio",
        "--log-level",
        "DEBUG",
        "--api-url",
        "https://ksr.canary-orion.keboola.dev/api"
      ],
      "env": {
        "SKILL_REGISTRY_TOKEN": "SKILL_GROUP_TOKEN_FROM_REGISTRY_SERVICE",
        "PYTHONPATH": "/path/to/keboola-skill-registry-mcp-server/src"
      }
    }
  }
}

Replace:

• /path/to/keboola-skill-registry-mcp-server with your actual path to the cloned repository
• SKILL_GROUP_TOKEN_FROM_REGISTRY_SERVICE with your skill registry API token

Troubleshooting

If you encounter an "ENOENT" error or "Could not connect to MCP server skill_registry":

1. Verify your Python path is correct and points to an executable that exists
2. Ensure the keboola.skill_registry_mcp package is installed in that Python environment
3. Try using the full absolute path to Python as shown in Option 1
4. Check if your Python environment has access to the installed package
5. If using Option 2, verify the command is in your PATH by running which keboola-sr-mcp (macOS/Linux) or where keboola-sr-mcp (Windows)

Available Tools

The server will include all tools that are exposed for the particular Skill Registry token. These tools will be automatically available to Claude when the MCP server is properly configured.

Development

To contribute to this project:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests: pytest
5. Submit a pull request

License

MIT License - see LICENSE file for details.