intermediate⏱️ 14-24 minutes📅 Updated June 2026

Step-by-step guide to integrate Apache Pinot MCP server with MCPOmni-Connect. Includes table management and segment management.

Apache Pinot + MCPOmni-Connect: 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 MCPOmni-Connect, 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 MCPOmni-Connect, 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 MCPOmni-Connect
  • 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
  • MCPOmni-Connect installed and configured
  • Compatible operating system (Python 3.9+, Windows, macOS, Linux, Docker)

Installation

Step 1: Install Apache Pinot

Configuration

Step 2: Configure MCPOmni-Connect

  1. Open MCPOmni-Connect 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 MCPOmni-Connect:

List All Tables

Get overview of available Pinot tables

Ask MCPOmni-Connect: "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 MCPOmni-Connect: "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 MCPOmni-Connect: "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 MCPOmni-Connect: "Create a histogram showing user activity distribution by hour"

Expected Result: Histogram visualization with data aggregated by time buckets

Testing Your Setup

  1. Launch MCPOmni-Connect
  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:

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

Command Not Found

Symptoms: mcpomni-connect: command not found, CLI not accessible

Cause: Package not installed or not in PATH

Solution:

  • Verify installation: pip show mcpomni-connect
  • Ensure Python scripts directory is in PATH
  • Try running with python -m: python -m mcpomni_connect
  • Reinstall: pip install --upgrade mcpomni-connect

Configuration File Not Found

Symptoms: FileNotFoundError: mcp_config.yaml, Config not loading

Cause: Config file missing or incorrect path

Solution:

  • Verify config file exists at specified path
  • Use absolute path: --config /full/path/to/mcp_config.yaml
  • Check file name is exactly mcp_config.yaml (case-sensitive)
  • Validate YAML syntax with yamllint or online validator

MCP Server Connection Failures

Symptoms: Server not responding, Connection timeout, Transport error

Cause: Invalid server configuration or transport issues

Solution:

  • Verify transport type matches server capabilities (stdio, sse, http, docker, npx)
  • For stdio: ensure command and args are correct
  • For SSE/HTTP: verify URL is accessible and server is running
  • For Docker: ensure Docker daemon is running and image exists
  • Check environment variables are set (e.g., GITHUB_TOKEN)
  • Test server manually outside MCPOmni-Connect

Agent Mode Not Working

Symptoms: Agent fails to execute task, Reasoning loop errors, Tool calls failing

Cause: Insufficient LLM configuration or tool access issues

Solution:

  • Ensure LLM API key is configured (OpenAI, Anthropic, etc.)
  • Verify agent has access to necessary MCP server tools
  • Check task description is clear and actionable
  • Review agent logs for detailed error messages
  • Try simpler task first to verify agent functionality

Orchestrator Mode Failures

Symptoms: Plan execution fails, Step coordination errors, Agent communication issues

Cause: Invalid plan structure or agent dependencies

Solution:

  • Verify plan steps are clearly defined and sequential
  • Ensure each step can be completed with available tools
  • Check inter-agent communication is working
  • Review orchestrator logs for step-by-step execution details
  • Test individual plan steps in agent mode first

Docker Transport Errors

Symptoms: Container not starting, Docker connection refused, Port binding errors

Cause: Docker configuration or runtime issues

Solution:

  • Verify Docker is installed and running: docker ps
  • Check Docker image exists: docker images
  • Ensure ports are not already in use
  • Review container logs: docker logs <container_name>
  • Verify network configuration allows container communication

FastAPI Integration Issues

Symptoms: Import errors, Async execution failures, Endpoint not responding

Cause: Incorrect async configuration or FastAPI version mismatch

Solution:

  • Use run_agent_async() for async FastAPI endpoints
  • Ensure FastAPI version is compatible (0.100.0+)
  • Verify MCPOmniClient is initialized outside request handlers
  • Check async event loop configuration
  • Review FastAPI logs for detailed error messages

Apache Pinot not appearing in MCPOmni-Connect

Symptoms: Server not listed, Tools not available

Cause: Configuration or installation issue

Solution:

  • Verify configuration syntax
  • Check Apache Pinot installation
  • Restart MCPOmni-Connect
  • Check logs for error messages

Next Steps

Now that Apache Pinot is integrated with MCPOmni-Connect:

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

Need Help?

Related Resources

More Integrations

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Need Help?

Join the MCP community for support and discussions

Apache Pinot + MCPOmni-Connect: MCP Setup Guide (2026)