# Kedro RAG MCP
## Prerequisites
- Python 3.8+
- Claude Desktop app (Get from website)
## Step 1: Clone and Set Up the Project
```bash
# 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
```bash
# 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:
```yaml
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
```bash
# 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:
```json
{
"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**:
```json
{
"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:
```bash
# 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.
<img width="1005" height="738" alt="image" src="https://github.com/user-attachments/assets/5fdcdbfe-c59a-4c38-9383-08cd47ab5f6e" />
