✨ Shopping Tool: MCP Server

mcp/README.md

@@ -0,0 +1,270 @@
+# MCP Tools
+
+This directory contains Model Context Protocol (MCP) tools that can be used by AI assistants and agents.
+
+## Available Tools
+
+### 1. Weather Tool (`weather_tool/`)
+
+Get weather information for any city.
+
+**Features**:
+- Current weather data
+- Temperature, wind speed, conditions
+- Uses Open-Meteo API (no API key required)
+
+**Tools**:
+- `get_weather(city: str)` - Get weather info for a city
+
+### 2. Movie Tool (`movie_tool/`)
+
+Get movie information and reviews from OMDb.
+
+**Features**:
+- Movie details (plot, ratings, actors, awards)
+- Full plot summaries
+- Uses OMDb API
+
+**Tools**:
+- `get_full_plot(movie_title: str)` - Get full plot summary
+- `get_movie_details(movie_title: str)` - Get full movie details
+
+**Requirements**:
+- OMDB_API_KEY environment variable
+
+### 3. Slack Tool (`slack_tool/`)
+
+Interact with Slack workspaces.
+
+**Features**:
+- List channels
+- Get channel history
+- Optional fine-grained authorization
+
+**Tools**:
+- `get_channels()` - Lists all public and private channels
+- `get_channel_history(channel_id: str, limit: int)` - Fetches recent messages
+
+**Requirements**:
+- SLACK_BOT_TOKEN environment variable
+- Optional: ADMIN_SLACK_BOT_TOKEN for fine-grained auth
+
+### 4. GitHub Tool (`github_tool/`)
+
+Interact with GitHub repositories (written in Go).
+
+**Features**:
+- Repository management
+- Issue tracking
+- Pull request operations
+
+**Requirements**:
+- GitHub authentication token
+
+### 5. Shopping Agent (`shopping_tool/`) ⭐ NEW
+
+AI-powered shopping recommendations using LangChain, LangGraph, OpenAI, and SerpAPI.
+
+**Features**:
+- Natural language query understanding
+- Real-time product search across retailers
+- AI-curated recommendations with reasoning
+- Budget-aware suggestions
+- Multi-step LangGraph workflow
+
+**Tools**:
+- `recommend_products(query: str, maxResults: int)` - Get AI-powered product recommendations
+- `search_products(query: str, maxResults: int)` - Raw product search
+
+**Requirements**:
+- OPENAI_API_KEY environment variable
+- SERPAPI_API_KEY environment variable
+
+**Example Usage**:
+```bash
+curl -X POST http://localhost:8000/tools/recommend_products \
+  -H "Content-Type: application/json" \
+  -d '{
+    "query": "I want to buy a scarf for 40 dollars",
+    "maxResults": 5
+  }'
+```
+
+**Technologies**:
+- FastMCP - MCP server framework
+- OpenAI GPT-4o-mini - Natural language understanding/generation
+- SerpAPI - Product search across retailers
+
+**Documentation**:
+- [README.md](shopping_agent/README.md) - Full documentation
+- [QUICKSTART.md](shopping_agent/QUICKSTART.md) - Quick start guide
+- [ARCHITECTURE.md](shopping_agent/ARCHITECTURE.md) - Architecture details
+
+## Getting Started
+
+### General Setup
+
+All MCP tools follow a similar pattern:
+
+1. **Install dependencies**:
+```bash
+cd <tool_directory>
+uv pip install -e .
+```
+
+2. **Configure environment variables**:
+```bash
+export API_KEY="your-api-key-here"
+```
+
+3. **Run the server**:
+```bash
+python <tool_name>.py
+```
+
+4. **Test the server**:
+```bash
+curl http://localhost:8000/health
+```
+
+### Docker Deployment
+
+Each tool includes a Dockerfile for containerized deployment:
+
+```bash
+cd <tool_directory>
+docker build -t <tool-name>-mcp .
+docker run -p 8000:8000 -e API_KEY="your-key" <tool-name>-mcp
+```
+
+## MCP Protocol
+
+All tools expose functionality via the Model Context Protocol (MCP), which allows AI assistants to discover and use these tools programmatically.
+
+### Key Features
+
+- **Tool Discovery**: Tools are self-describing with metadata
+- **Type Safety**: Strong typing for parameters and returns
+- **Documentation**: Built-in documentation for each tool
+- **Error Handling**: Standardized error responses
+- **Transport**: HTTP transport support (streamable HTTP optional)
+
+### Tool Annotations
+
+Tools use annotations to describe their behavior:
+- `readOnlyHint`: Indicates if the tool only reads data
+- `destructiveHint`: Warns if the tool modifies or deletes data
+- `idempotentHint`: Indicates if repeated calls have the same effect
+
+## Framework Comparison
+
+| Tool | Language | Framework | Key Library |
+|------|----------|-----------|-------------|
+| Weather | Python | FastMCP | requests |
+| Movie | Python | FastMCP | requests + OMDb |
+| Slack | Python | FastMCP | slack_sdk |
+| GitHub | Go | Custom | GitHub API |
+| Shopping Agent | Python | FastMCP | SerpAPI |
+
+## Advanced Example: Shopping Agent Architecture
+
+The Shopping Agent demonstrates an advanced MCP tool with:
+
+```
+User Query
+    ↓
+SerpAPI Search
+    ↓
+Structured Response
+## Creating Your Own MCP Tool
+
+### Basic Template
+
+```python
+import os
+from fastmcp import FastMCP
+
+mcp = FastMCP("My Tool")
+
+@mcp.tool(annotations={"readOnlyHint": True})
+def my_function(param: str) -> str:
+    """Tool description"""
+    # Your logic here
+    return result
+
+def run_server():
+    transport = os.getenv("MCP_TRANSPORT", "http")
+    host = os.getenv("HOST", "0.0.0.0")
+    port = int(os.getenv("PORT", "8000"))
+    mcp.run(transport=transport, host=host, port=port)
+
+if __name__ == "__main__":
+    run_server()
+```
+
+### Best Practices
+
+1. **Environment Variables**: Use env vars for API keys and configuration
+2. **Error Handling**: Return structured error responses
+3. **Logging**: Use appropriate log levels
+4. **Documentation**: Include docstrings for all tools
+5. **Type Hints**: Use type hints for parameters and returns
+6. **Testing**: Provide test clients or scripts
+7. **Docker**: Include Dockerfile for deployment
+8. **README**: Comprehensive documentation
+
+## Common Environment Variables
+
+| Variable | Description | Default |
+|----------|-------------|---------|
+| HOST | Server host address | 0.0.0.0 |
+| PORT | Server port | 8000 |
+| MCP_TRANSPORT | Transport protocol | http |
+| LOG_LEVEL | Logging level | INFO |
+
+## Troubleshooting
+
+### Server Won't Start
+
+1. Check API keys are set
+2. Verify port 8000 is available
+3. Check Python version (3.10+)
+4. Review logs for errors
+
+### Tool Returns Errors
+
+1. Verify API keys are valid
+2. Check API quota limits
+3. Review request parameters
+4. Check network connectivity
+
+### Import Errors
+
+1. Install dependencies: `uv pip install -e .`
+2. Verify Python version
+3. Check for conflicting packages
+
+## Contributing
+
+When adding new MCP tools:
+
+1. Follow the existing structure
+2. Use FastMCP framework (or document why not)
+3. Include comprehensive README
+4. Add Dockerfile
+5. Provide test client
+6. Document all tools and parameters
+7. Use environment variables for secrets
+8. Add logging and error handling
+
+## Resources
+
+- [FastMCP Documentation](https://github.com/jlowin/fastmcp)
+- [Model Context Protocol Spec](https://modelcontextprotocol.io/)
+- [LangChain Documentation](https://python.langchain.com/)
+- [LangGraph Documentation](https://langchain-ai.github.io/langgraph/)
+
+## License
+
+See the repository's LICENSE file for details.
+

mcp/github_tool/README.md

@@ -137,7 +137,7 @@ After adding the new env vars, apply to Kagenti using `kubectl apply -n team1 -f
 Now that the environment variables are available, start an instance of the tool
 
 - Browse to http://kagenti-ui.localtest.me:8080/Import_New_Tool
-- Select namespace (e.g. `team1`)
+- Select namespace 
 - Set the Target Port to 9090
 - Specify Subfolder `mcp/github_tool`
 - Click "Build & Deploy New Tool" to deploy.

mcp/shopping_tool/.gitignore

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+# API Keys and Secrets - NEVER COMMIT THESE!
+.env
+.env.local
+.env.*.local
+config.sh
+*.key
+*.pem
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual Environments
+venv/
+ENV/
+env/
+.venv
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+.DS_Store
+
+# Logs
+*.log
+
+# Testing
+.pytest_cache/
+.coverage
+htmlcov/
+
+# uv
+uv.lock
+