Apache Pinot + Lutra AI: Complete MCP Integration
Apache Pinot is a MCP server that MCP server for Apache Pinot real-time analytics database with SQL query capabilities and metadata access.
When integrated with Lutra AI, you can:
- List and inspect Apache Pinot tables
- View and analyze table segments
- Retrieve and analyze table schemas
This guide provides step-by-step instructions to set up Apache Pinot in Lutra AI, including configuration, examples, and troubleshooting.
What You'll Achieve
After completing this setup:
- Apache Pinot will be fully integrated and operational
- You can use Apache Pinot tools directly in Lutra AI
- All Apache Pinot capabilities will be available for your workflows
- Access to 5 different tools
Prerequisites
Before starting, ensure you have:
- Apache Pinot broker hostname
- Apache Pinot broker port
- Lutra AI installed and configured
- Compatible operating system (Web Platform, Mobile Web)
Installation
Step 1: Install Apache Pinot
Configuration
Step 2: Configure Lutra AI
- Open Lutra AI settings
- Navigate to MCP server configuration
- Add Apache Pinot server with appropriate settings
- Save and restart if needed
Examples
Once configured, you can use Apache Pinot in Lutra AI:
List All Tables
Get overview of available Pinot tables
Ask Lutra AI: "Show me all the tables available in the Pinot cluster"
Expected Result: List of table names with basic metadata and schema information
Execute Analytics Query
Run SQL query for real-time analytics
Ask Lutra AI: "SELECT COUNT(*) FROM events WHERE timestamp > now() - 3600000"
Expected Result: Query results showing event count for last hour
Analyze Table Structure
Get detailed schema information for a table
Ask Lutra AI: "Show me the schema and structure of the user_events table"
Expected Result: Table schema with column names, types, and index information
Generate Data Visualization
Create histogram plots from query results
Ask Lutra AI: "Create a histogram showing user activity distribution by hour"
Expected Result: Histogram visualization with data aggregated by time buckets
Testing Your Setup
- Start a new conversation in Lutra AI
- Ask Lutra AI to list available tools
- Try using Apache Pinot functionality
Troubleshooting
Common Issues
uv Command Not Found
Symptoms: Command not found error, uv: command not found
Cause: uv package manager not installed
Solution:
- Install uv using: curl -LsSf https://astral.sh/uv/install.sh | sh
- Restart terminal or source shell configuration
- Verify installation with: uv --version
Pinot Connection Failed
Symptoms: Connection refused, Broker unreachable, Network timeout
Cause: Invalid Pinot broker configuration or cluster not running
Solution:
- Verify PINOT_BROKER_HOST and PINOT_BROKER_PORT in .env file
- Check Pinot cluster is running and accessible
- Test connection: telnet <broker_host> <broker_port>
- Ensure firewall allows connections to Pinot broker
Environment Variables Not Loaded
Symptoms: Config missing errors, Default values being used
Cause: .env file not found or incorrectly formatted
Solution:
- Create .env file in repository root directory
- Copy from .env.example and modify values
- Ensure no spaces around = in variable assignments
- Restart MCP server after configuration changes
Claude Desktop Not Recognizing Server
Symptoms: Server not appearing, Connection errors in Claude
Cause: Incorrect claude_desktop_config.json configuration
Solution:
- Verify path to uv binary in command field
- Ensure correct path to mcp-pinot repository
- Restart Claude Desktop after configuration changes
- Check Claude Desktop logs for error messages
MCP Server Not Connecting
Symptoms: Server not appearing in connections, Connection timeout, Unable to reach server
Cause: Invalid server URL or server not accessible
Solution:
- Verify MCP server URL is correct and accessible
- Check server is running and responding to requests
- Ensure server supports HTTP/SSE transport (Lutra requirement)
- Test server URL in browser or with curl to confirm accessibility
- Contact Lutra support if server should be compatible
Authentication Failures
Symptoms: OAuth errors, Permission denied, Unauthorized access
Cause: OAuth not configured or credentials expired
Solution:
- Complete OAuth authorization flow for connected apps
- Refresh expired credentials through connections panel
- Verify required permissions are granted for each app
- Disconnect and reconnect app if authentication persists
Lutra Not Understanding Tasks
Symptoms: Incorrect task execution, Lutra asks for clarification repeatedly, Wrong app or tool used
Cause: Ambiguous instructions or insufficient context
Solution:
- Provide clear, specific instructions with context
- Specify which app or MCP server to use if ambiguous
- Break complex tasks into smaller, clearer steps
- Use examples or reference previous successful tasks
Playbooks Not Working
Symptoms: Playbook execution fails, Different results than expected, Missing steps
Cause: Changed app configurations or unavailable resources
Solution:
- Review playbook steps to ensure they are still valid
- Update playbook if app configurations have changed
- Verify all connected apps and MCP servers are accessible
- Test playbook step-by-step to identify failure point
Workflow Automation Limits
Symptoms: Task quota exceeded, Automation disabled, Rate limiting
Cause: Plan limits reached or service rate limits
Solution:
- Check Lutra plan limits and current usage
- Upgrade plan if automation needs exceed current tier
- Optimize workflows to reduce unnecessary API calls
- Implement delays between rapid successive automations
Apache Pinot not appearing in Lutra AI
Symptoms: Server not listed, Tools not available
Cause: Configuration or installation issue
Solution:
- Verify configuration syntax
- Check Apache Pinot installation
- Restart Lutra AI
- Check logs for error messages
Next Steps
Now that Apache Pinot is integrated with Lutra AI:
- Explore all Apache Pinot capabilities through Lutra AI
- Check out other MCP servers that work with Lutra AI
- Join the MCP community for tips and support
- Consider contributing to Apache Pinot development
Need Help?
- Search for Apache Pinot documentation
- Check the Lutra AI MCP guide
- Join the MCP community discussions