Kedro RAG MCP

Prerequisites

• Python 3.8+

• Claude Desktop app (Get from website)

Related MCP server: mcp-rag-server

Step 1: Clone and Set Up the Project

# Clone your repository
git clone https://github.com/your-username/kedro-mcp-rag.git
cd kedro-mcp-rag

# Create a virtual environment (using conda) 
conda create -n kedro-rag python=3.12 -y
conda activate kedro-rag

# Or using venv
python -m venv venv
source venv/bin/activate

Step 2: Install Dependencies

# Install the RAG system dependencies
pip install -r requirements.txt

Step 3: Set Up Kedro Documentation with llms.txt

3.1 Clone Kedro Repository (if not already done)

3.2 Update mkdocs.yml Configuration (if not already done)

The Kedro mkdocs.yml should have the llmstxt plugin configured:

plugins:
  # ... other plugins ...
  - llmstxt:
      markdown_description: |
        Kedro is an open-source Python framework for creating reproducible, maintainable, and modular data science code. 
        # ... rest of description ...
      full_output: llms-full.txt
      sections:
        # ... sections configuration ...

3.3 Serve the Documentation

# In the kedro directory
make serve-docs

This will:

• Start the documentation server at http://127.0.0.1:8000

• Generate the llms-full.txt file at http://127.0.0.1:8000/en/stable/llms-full.txt

Important: Keep this server running while using the RAG system!

Step 4: Configure Claude Desktop

4.1 Locate Claude Desktop Config

The config file location varies by OS:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

4.2 Update the Configuration

Edit claude_desktop_config.json and add your MCP server configuration:

{
  "mcpServers": {
    "kedro-assistant": {
      "command": "/path/to/your/python",
      "args": ["/path/to/kedro-mcp-rag/kedro_mcp.py"],
      "env": {
        "PYTHONPATH": "/path/to/kedro-mcp-rag/"
      }
    }
  }
}

Replace the paths with your actual paths. For example:

• macOS with Anaconda:

  {
    "mcpServers": {
      "kedro-assistant": {
        "command": "/Users/YourName/anaconda3/envs/kedro-rag/bin/python",
        "args": ["/Users/YourName/GitHub/kedro-mcp-rag/kedro_mcp.py"],
        "env": {
          "PYTHONPATH": "/Users/YourName/GitHub/kedro-mcp-rag/"
        }
      }
    }
  }

To find the correct Python path:

# With conda environment activated
which python  # macOS/Linux

# Or
conda info --envs  # Shows all conda environments

Step 5: Test the Setup

5.1 Restart Claude Desktop

1. Completely quit Claude Desktop

2. Restart Claude Desktop

3. The MCP tools should now be available

4. Ask it a kedro related question and it will use the tools to build knowledge DB at /tmp/kedro_knowledge_db if it doesn't already exist.

5. If you see the following in Claude Desktop settings then MCP is up and running with the RAG.