Apache Pinot + gptme: 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 gptme, 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 gptme, 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 gptme
• 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
• gptme installed and configured
• Compatible operating system (Terminal, Python, Cross-platform)

Installation

Step 1: Install Apache Pinot

Configuration

Step 2: Configure gptme

1. Open gptme settings
2. Navigate to MCP server configuration
3. Add Apache Pinot server with appropriate settings
4. Save and restart if needed

Examples

Once configured, you can use Apache Pinot in gptme:

List All Tables

Get overview of available Pinot tables

Ask gptme: "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 gptme: "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 gptme: "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 gptme: "Create a histogram showing user activity distribution by hour"

Expected Result: Histogram visualization with data aggregated by time buckets

Testing Your Setup

1. Launch gptme
2. Verify Apache Pinot is available in the tools list
3. Test basic 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

Installation Failed

Symptoms: pip install errors, Missing dependencies

Cause: Python environment or package conflicts

Solution:

• Use virtual environment for clean installation
• Update pip to latest version
• Install with pipx for isolation
• Check Python version compatibility

API Key Issues

Symptoms: Authentication errors, Model access denied

Cause: Missing or invalid API keys

Solution:

• Verify API keys are set correctly
• Check API key permissions and quotas
• Test API keys with curl or other tools
• Review model provider documentation

MCP Server Not Loading

Symptoms: Server load errors, Tools not available

Cause: Server configuration or installation issues

Solution:

• Verify server installation and PATH
• Check MCP server configuration syntax
• Test server independently before gptme integration
• Review gptme logs for connection errors

Terminal Display Issues

Symptoms: Formatting problems, Character encoding errors

Cause: Terminal compatibility or encoding issues

Solution:

• Ensure terminal supports UTF-8 encoding
• Try different terminal applications
• Check terminal color and formatting settings
• Update terminal application to latest version

Apache Pinot not appearing in gptme

Symptoms: Server not listed, Tools not available

Cause: Configuration or installation issue

Solution:

• Verify configuration syntax
• Check Apache Pinot installation
• Restart gptme
• Check logs for error messages

Next Steps

Now that Apache Pinot is integrated with gptme:

• Explore all Apache Pinot capabilities through gptme
• Check out other MCP servers that work with gptme
• Join the MCP community for tips and support
• Consider contributing to Apache Pinot development

Need Help?

• Search for Apache Pinot documentation
• Check the gptme MCP guide
• Join the MCP community discussions