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NL Analytics MCP Server for Apache Druid

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Druid MCP Server

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A comprehensive Model Context Protocol (MCP) server for Apache Druid that provides extensive tools, resources, and prompts for managing and analyzing Druid clusters.

Developed by

Overview

This MCP server implements a feature-based architecture where each package represents a distinct functional area of Druid management. The server provides three main types of MCP components:

  • Tools - Executable functions for performing operations

  • Resources - Data providers for accessing information

  • Prompts - AI-assisted guidance templates

Video Walkthrough

Learn how to integrate AI agents with Apache Druid using the MCP server. This tutorial demonstrates time series data exploration, statistical analysis, and data ingestion using natural language with AI assistants like Claude, ChatGPT, and Gemini.

Time Series on AI Steroids: Apache Druid Enterprise MCP Server Tutorial

Click the thumbnail above to watch the video on YouTube

Features

  • Spring AI MCP Server integration

  • Tool-based architecture for MCP protocol compliance

  • Tool-based Architecture: Complete MCP protocol compliance with automatic JSON schema generation

  • Multiple Transport Modes: STDIO, SSE, and Streamable HTTP support

  • Real-time Communication: Server-Sent Events with streaming capabilities

  • Comprehensive error handling

  • Customizable Prompt Templates: AI-assisted guidance with template customization

  • Comprehensive Error Handling: Graceful error handling with meaningful responses

Architecture & Organization

  • Feature-based Package Organization: Each package represents a distinct Druid management area

  • Auto-discovery: Automatic registration of tools, resources, and prompts via annotations

  • Enterprise Ready: Production-grade configuration and security features

MCP Inspector Interface

When connected to an MCP client, you can inspect the available tools, resources, and prompts through the MCP inspector interface:

Available Tools

MCP Inspector - Tools

The tools interface shows all available Druid management functions organized by feature areas including data management, ingestion management, and monitoring & health.

Available Resources

MCP Inspector - Resources

The resources interface displays all accessible Druid data sources and metadata that can be retrieved through the MCP protocol.

Available Prompts

MCP Inspector - Prompts

The prompts interface shows all AI-assisted guidance templates available for various Druid management tasks and data analysis workflows.

Quick Start

MCP Configuration for LLMs

A ready-to-use MCP configuration file is provided at mcp-servers-config.json that can be used with LLM clients to connect to this Druid MCP server.

Examples

The configuration includes both transport options:

  • STDIO: STDIO-based streaming connection via command-line.

  • SSE: HTTP-based streaming connection via Server-Sent Events.

  • Streamable HTTP Configuration Modern single-endpoint HTTP transport per MCP 2025-06-18.

Docker examples using environment variables:

# Run with SSE Transport (HTTP-based, default) docker run -p 8080:8080 \ -e DRUID_ROUTER_URL=http://your-druid-router:8888 \ iunera/druid-mcp-server:latest # OR run with STDIO Transport (recommended for LLM clients) docker run --rm -i \ -e SPRING_AI_MCP_SERVER_STDIO=true \ -e SPRING_MAIN_WEB_APPLICATION_TYPE=none \ -e LOGGING_PATTERN_CONSOLE= \ -e DRUID_ROUTER_URL=http://your-druid-router:8888 \ iunera/druid-mcp-server:latest

Prerequisites

  • Java 24

  • Maven 3.6+

  • Apache Druid cluster running with router on port 8888

Build and Run

# Build the application mvn clean package -DskipTests # Run the application java -jar target/druid-mcp-server-1.2.2.jar

The server will start on port 8080 by default.

For detailed build instructions, testing, Docker setup, and development guidelines, see development.md.

Installation from Maven Central

If you prefer to use the pre-built JAR without building from source, you can download and run it directly from Maven Central.

Prerequisites

  • Java 24 JRE only

Download and Run

Download the JAR from Maven Central https://repo.maven.apache.org/maven2/com/iunera/druid-mcp-server/

# Run with SSE Transport (HTTP-based, default) java -jar druid-mcp-server-1.2.2.jar # OR run with STDIO Transport (recommended for LLM clients) java -Dspring.ai.mcp.server.stdio=true \ -Dspring.main.web-application-type=none \ -Dlogging.pattern.console= \ -jar druid-mcp-server-1.2.2.jar

For Developers

For detailed development information including build instructions, testing guidelines, architecture details, and contributing guidelines, see development.md.

Available Tools by Feature

The MCP server auto-discovers all tools via annotations. In Read-only mode, any tool that would modify the Druid cluster is not registered and will not appear in the MCP client. The lists below reflect the current implementation.

Data Management

Feature

Tool

Description

Parameters

Datasource

listDatasources

List all available Druid datasource names

None

Datasource

showDatasourceDetails

Show detailed information for a specific datasource including column information

datasourceName

(String)

Datasource

killDatasource

Kill a datasource permanently, removing all data and metadata

datasourceName

(String),

interval

(String)

Lookup

listLookups

List all available Druid lookups from the coordinator

None

Lookup

getLookupConfig

Get configuration for a specific lookup

tier

(String),

lookupName

(String)

Lookup

updateLookupConfig

Update configuration for a specific lookup

tier

(String),

lookupName

(String),

config

(String)

Segments

listAllSegments

List all segments across all datasources

None

Segments

getSegmentMetadata

Get metadata for specific segments

datasourceName

(String),

segmentId

(String)

Segments

getSegmentsForDatasource

Get all segments for a specific datasource

datasourceName

(String)

Query

queryDruidSql

Execute a SQL query against Druid datasources

sqlQuery

(String)

Retention

viewRetentionRules

View retention rules for all datasources or a specific one

datasourceName

(String, optional)

Retention

updateRetentionRules

Update retention rules for a datasource

datasourceName

(String),

rules

(String)

Compaction

viewAllCompactionConfigs

View compaction configurations for all datasources

None

Compaction

viewCompactionConfigForDatasource

View compaction configuration for a specific datasource

datasourceName

(String)

Compaction

editCompactionConfigForDatasource

Edit compaction configuration for a datasource

datasourceName

(String),

config

(String)

Compaction

deleteCompactionConfigForDatasource

Delete compaction configuration for a datasource

datasourceName

(String)

Compaction

viewCompactionStatus

View compaction status for all datasources

None

Compaction

viewCompactionStatusForDatasource

View compaction status for a specific datasource

datasourceName

(String)

Ingestion Management

Feature

Tool

Description

Parameters

Ingestion Spec

createBatchIngestionTemplate

Create a batch ingestion template

datasourceName

(String),

inputSource

(String),

timestampColumn

(String)

Ingestion Spec

createIngestionSpec

Create and submit an ingestion specification

specJson

(String)

Supervisors

listSupervisors

List all streaming ingestion supervisors

None

Supervisors

getSupervisorStatus

Get status of a specific supervisor

supervisorId

(String)

Supervisors

suspendSupervisor

Suspend a streaming supervisor

supervisorId

(String)

Supervisors

startSupervisor

Start or resume a streaming supervisor

supervisorId

(String)

Supervisors

terminateSupervisor

Terminate a streaming supervisor

supervisorId

(String)

Tasks

listTasks

List all ingestion tasks

None

Tasks

getTaskStatus

Get status of a specific task

taskId

(String)

Tasks

shutdownTask

Shutdown a running task

taskId

(String)

Monitoring & Health

Feature

Tool

Description

Parameters

Basic Health

checkClusterHealth

Check overall cluster health status

None

Basic Health

getServiceStatus

Get status of specific Druid services

serviceType

(String)

Basic Health

getClusterConfiguration

Get cluster configuration information

None

Diagnostics

runDruidDoctor

Run comprehensive cluster diagnostics

None

Diagnostics

analyzePerformanceIssues

Analyze cluster performance issues

None

Diagnostics

generateHealthReport

Generate detailed health report

None

Functionality

testQueryFunctionality

Test query functionality across services

None

Functionality

testIngestionFunctionality

Test ingestion functionality

None

Functionality

validateClusterConnectivity

Validate connectivity between cluster components

None

Available Resources by Feature

Feature

Resource URI Pattern

Description

Parameters

Datasource

druid://datasource/{datasourceName}

Access datasource information and metadata

datasourceName

(String)

Datasource

druid://datasource/{datasourceName}/details

Access detailed datasource information including schema

datasourceName

(String)

Lookup

druid://lookup/{tier}/{lookupName}

Access lookup configuration and data

tier

(String),

lookupName

(String)

Segments

druid://segment/{segmentId}

Access segment metadata and information

segmentId

(String)

Available Prompts by Feature

Feature

Prompt Name

Description

Parameters

Data Analysis

data-exploration

Guide for exploring data in Druid datasources

datasource

(String, optional)

Data Analysis

query-optimization

Help optimize Druid SQL queries for better performance

query

(String)

Cluster Management

health-check

Comprehensive cluster health assessment guidance

None

Cluster Management

cluster-overview

Overview and analysis of cluster status

None

Ingestion Management

ingestion-troubleshooting

Troubleshoot ingestion issues

issue

(String, optional)

Ingestion Management

ingestion-setup

Guide for setting up new ingestion pipelines

dataSource

(String, optional)

Retention Management

retention-management

Manage data retention policies

datasource

(String, optional)

Compaction

compaction-suggestions

Optimize segment compaction configuration

datasource

(String, optional),

currentConfig

(String, optional),

performanceMetrics

(String, optional)

Compaction

compaction-troubleshooting

Troubleshoot compaction issues

issue

(String),

datasource

(String, optional)

Operations

emergency-response

Emergency response procedures and guidance

None

Operations

maintenance-mode

Cluster maintenance procedures

None

Environment Variables Configuration

For sensitive credentials like username and password, you can use environment variables instead of hardcoding them in properties files.

Supported Environment Variables

  • DRUID_AUTH_USERNAME: Druid authentication username

  • DRUID_AUTH_PASSWORD: Druid authentication password

  • DRUID_ROUTER_URL: Override the default Druid router URL

  • DRUID_SSL_ENABLED: Enable SSL/TLS support (true/false)

  • DRUID_SSL_SKIP_VERIFICATION: Skip SSL certificate verification (true/false)

SSL-Encrypted Cluster with Authentication

This section provides comprehensive guidance on connecting to SSL-encrypted Druid clusters with username and password authentication.

Prerequisites

  • SSL-enabled Druid cluster with HTTPS endpoints

  • Valid username and password credentials for Druid authentication

  • SSL certificates properly configured (or ability to skip verification for testing)

Configuration Methods

Method 1: Environment Variables (Recommended for Production)

Set the following environment variables before starting the MCP server:

# Druid cluster URL with HTTPS export DRUID_ROUTER_URL="https://your-druid-cluster.example.com:8888" # Authentication credentials export DRUID_AUTH_USERNAME="your-username" export DRUID_AUTH_PASSWORD="your-password" # SSL configuration export DRUID_SSL_ENABLED="true" export DRUID_SSL_SKIP_VERIFICATION="false" # Use "true" only for testing # Start the MCP server java -jar target/druid-mcp-server-1.2.2.jar
Method 2: Runtime System Properties

Pass configuration as JVM system properties:

java -Ddruid.router.url="https://your-druid-cluster.example.com:8888" \ -Ddruid.auth.username="your-username" \ -Ddruid.auth.password="your-password" \ -Ddruid.ssl.enabled=true \ -Ddruid.ssl.skip-verification=false \ -jar target/druid-mcp-server-1.2.2.jar

SSL Configuration Options

Production SSL Setup

For production environments with valid SSL certificates:

export DRUID_ROUTER_URL="https://druid-prod.company.com:8888" export DRUID_SSL_ENABLED="true" export DRUID_SSL_SKIP_VERIFICATION="false"

The server will use the system's default truststore to validate SSL certificates.

Authentication Methods

The MCP server supports HTTP Basic Authentication with username and password:

  • Username: Set via DRUID_AUTH_USERNAME or druid.auth.username

  • Password: Set via DRUID_AUTH_PASSWORD or druid.auth.password

The credentials are automatically encoded using Base64 and sent with each request using the Authorization: Basic header.

MCP Client Configuration with SSL

Update your mcp-servers-config.json to include environment variables:

{ "mcpServers": { "druid-mcp-server": { "command": "docker", "args": [ "run", "--rm", "-i", "-e", "SPRING_AI_MCP_SERVER_STDIO=true", "-e", "SPRING_MAIN_WEB_APPLICATION_TYPE=none", "-e", "LOGGING_PATTERN_CONSOLE=", "-e", "DRUID_ROUTER_URL", "-e", "DRUID_AUTH_USERNAME", "-e", "DRUID_AUTH_PASSWORD", "-e", "DRUID_SSL_ENABLED", "-e", "DRUID_SSL_SKIP_VERIFICATION", "-e", "DRUID_MCP_READONLY", "iunera/druid-mcp-server:1.2.2" ], "env": { "DRUID_ROUTER_URL": "http://host.docker.internal:8888", "DRUID_AUTH_USERNAME": "", "DRUID_AUTH_PASSWORD": "", "DRUID_SSL_ENABLED": "false", "DRUID_SSL_SKIP_VERIFICATION": "true", "DRUID_MCP_READONLY": "false" } } } }

MCP Prompt Customization

The server provides extensive prompt customization capabilities through the prompts.properties file located in src/main/resources/.

Prompt Configuration Structure

The prompts.properties file contains:

  1. Global Settings: Enable/disable prompts and set watermarks

  2. Feature Toggles: Control which prompts are available

  3. Custom Variables: Organization-specific information

  4. Template Definitions: Full prompt templates for each feature

Overriding Prompts

You can override any prompt template using Java system properties with the -D flag:

Method 1: System Properties (Runtime Override)

java -Dprompts.druid-data-exploration.template="Your custom template here" \ -jar target/druid-mcp-server-1.2.2.jar

Method 2: Custom Properties File

  1. Create a custom properties file (e.g., custom-prompts.properties):

# Custom prompt template prompts.druid-data-exploration.template=My custom data exploration prompt:\n\ 1. Custom step one\n\ 2. Custom step two\n\ {datasource_section}\n\ Environment: {environment}

  1. Load it at runtime:

java -Dspring.config.additional-location=classpath:custom-prompts.properties \ -jar target/druid-mcp-server-1.2.2.jar

Available Prompt Variables

All prompt templates support these variables:

Variable

Description

Example

{environment}

Current environment name

production

,

staging

,

dev

{organizationName}

Organization name

Your Organization

{contactInfo}

Contact information

your-team@company.com

{watermark}

Generated watermark

Generated by Druid MCP Server v1.0.0

{datasource}

Datasource name (context-specific)

sales_data

{query}

SQL query (context-specific)

SELECT * FROM sales_data

Prompt Template Examples

Custom Data Exploration Prompt

prompts.druid-data-exploration.template=Welcome to {organizationName} Druid Analysis!\n\n\ Please help me explore our data:\n\ {datasource_section}\n\ Environment: {environment}\n\ Contact: {contactInfo}\n\n\ {watermark}

Custom Query Optimization Prompt

prompts.druid-query-optimization.template=Query Performance Analysis for {organizationName}\n\n\ Query to optimize: {query}\n\n\ Please provide:\n\ 1. Performance bottleneck analysis\n\ 2. Optimization recommendations\n\ 3. Best practices for our {environment} environment\n\n\ {watermark}

Disabling Specific Prompts

You can disable individual prompts by setting their enabled flag to false:

mcp.prompts.data-exploration.enabled=false mcp.prompts.query-optimization.enabled=false

Or disable all prompts globally:

mcp.prompts.enabled=false

MCP Integration

This server uses Spring AI's MCP Server framework and supports both STDIO and SSE transports. The tools, resources, and prompts are automatically registered and exposed through the MCP protocol.

Transport Modes

The Druid MCP Server supports multiple transport modes compliant with MCP 2025-06-18 specification:

Streamable HTTP Transport (Recommended and Default - New in MCP 2025-06-18)

The new Streamable HTTP transport provides enhanced performance and scalability with support for multiple concurrent clients:

# Default configuration with Streamable HTTP java -Dspring.ai.mcp.server.stdio=true \ -Dspring.main.web-application-type=none \ -Dlogging.pattern.console= \ -jar target/druid-mcp-server-1.2.2.jar # Server available at http://localhost:8080/mcp (configurable endpoint)

Note: The -Dspring.ai.mcp.server.protocol option is deprecated and no longer required. STREAMABLE is the default protocol and is configured in application.properties. If you previously set this flag, you can safely remove it.

Features:

  • Single Endpoint: One HTTP endpoint handles both POST and GET requests

  • Multiple Clients: Support for concurrent client connections

  • Optional SSE Streaming: Server-Sent Events for real-time updates

  • Enhanced Security: Origin header validation and authentication

  • Backwards Compatibility: Automatic fallback for older MCP clients

  • Keep-alive: Configurable connection health monitoring

STDIO Transport (Command-line Integration)

Perfect for LLM clients and desktop applications:

java -Dspring.ai.mcp.server.stdio=true \ -Dspring.main.web-application-type=none \ -Dlogging.pattern.console= \ -jar target/druid-mcp-server-1.2.2.jar

Legacy SSE Transport (Deprecated)

Still supported for backwards compatibility. It is no longer the default and may be removed in a future version.

java -jar target/druid-mcp-server-1.2.2.jar # Server available at http://localhost:8080/sse

Read-only Mode

Read-only mode prevents any operation that could mutate your Druid cluster while still allowing safe read operations and SQL queries. When enabled:

  • All HTTP GET requests are allowed

  • HTTP POST is allowed only to the exact path /druid/v2/sql (for SELECT and other read-only SQL)

  • Any other HTTP method (PUT, PATCH, DELETE) is blocked

  • Any other POST endpoint (e.g. ingestion/task endpoints) is blocked

  • MCP write tools are not registered, so they will not appear in your MCP client’s tool list

Enable Read-only Mode

You can enable it using any of the following methods:

  1. application.properties

druid.mcp.readonly.enabled=true

  1. Environment variable

export DRUID_MCP_READONLY_ENABLED=true

  1. JVM system property

java -Ddruid.mcp.readonly.enabled=true -jar target/druid-mcp-server-1.2.2.jar

  1. Docker

docker run --rm -p 8080:8080 \ -e DRUID_ROUTER_URL=http://your-druid-router:8888 \ -e DRUID_MCP_READONLY_ENABLED=true \ iunera/druid-mcp-server:latest

What changes in read-only mode?

  • Tools that would modify the cluster are disabled and won’t be listed by the MCP client. Examples include:

    • Segment state changes (enableSegment, disableSegment)

    • Datasource deletion (killDatasource)

    • Retention rule edits (editRetentionRulesForDatasource)

    • Compaction config edits (editCompactionConfigForDatasource, deleteCompactionConfigForDatasource)

    • Lookup changes (createOrUpdateLookup, deleteLookup)

    • Supervisor control (suspendSupervisor, startSupervisor, terminateSupervisor)

    • Task control (killTask)

    • Multi-stage SQL task operations (queryDruidMultiStage, queryDruidMultiStageWithContext, getMultiStageQueryTaskStatus, cancelMultiStageQueryTask)

    • Ingestion spec submission and templates (createIngestionSpec, createBatchIngestionTemplate)

  • Read-only-safe tools remain available, including SQL queries (queryDruidSql), metadata and status lookups, health diagnostics, task and segment inspection, etc.

🐳 Druid Cluster Setup

Complete Docker Compose configuration for running a full Apache Druid cluster locally. Perfect for development, testing, and learning about Druid cluster architecture.

Features:

  • Full Druid cluster with all components (Coordinator, Broker, Historical, MiddleManager, Router)

  • PostgreSQL metadata storage and ZooKeeper coordination

  • Pre-configured with sample data and ingestion examples

  • Integrated Druid MCP Server for immediate testing

~~## Related Projects

This Druid MCP Server is part of a comprehensive ecosystem of Apache Druid tools and extensions developed by iunera. These complementary projects enhance different aspects of Druid cluster management and data ingestion:

🔧 Druid Cluster Configuration

Advanced configuration management and deployment tools for Apache Druid clusters. This project provides:

  • Automated Cluster Setup: Streamlined configuration templates for different deployment scenarios

  • Configuration Management: Best practices and templates for production Druid clusters

  • Deployment Automation: Tools and scripts for consistent cluster deployments

  • Environment-Specific Configs: Optimized configurations for development, staging, and production environments

Integration with Druid MCP Server: The cluster configurations provided by this project work seamlessly with the monitoring and management capabilities of the Druid MCP Server, enabling comprehensive cluster lifecycle management.

📊 Code Ingestion Druid Extension

A specialized Apache Druid extension for ingesting and analyzing code-related data and metrics. This extension enables:

  • Code Metrics Ingestion: Specialized parsers for code analysis data and software metrics

  • Developer Analytics: Tools for analyzing code quality, complexity, and development patterns

  • CI/CD Integration: Seamless integration with continuous integration and deployment pipelines

  • Custom Data Formats: Support for various code analysis tools and formats

Integration with Druid MCP Server: This extension expands the ingestion capabilities that can be managed through the MCP server's ingestion management tools, providing specialized support for code analytics use cases.

Why Use These Together?

  • Complete Ecosystem: From cluster setup to specialized data ingestion and management

  • Consistent Architecture: All projects follow similar design principles and integration patterns

  • Enhanced Capabilities: Each project extends different aspects of the Druid ecosystem

  • Production Ready: Battle-tested configurations and extensions for enterprise deployments

Roadmap

  • Authentication on SSE/HTTP Mode: Introduce Oauth Authentication

  • Druid Auto Compaction: Intelligent automatic compaction configuration

  • MCP Auto Completion: Enhanced autocomplete functionality with sampling using McpComplete

  • MCP Notifications: Real-time notifications for MCP operations

  • Proper Observability: Comprehensive metrics and tracing

  • Enhanced Monitoring: Advanced cluster monitoring and alerting capabilities

  • Advanced Analytics: Machine learning-powered insights and recommendations

  • Security Enhancements: Advanced authentication and authorization features

  • Kubernetes Support: Proper deployment on Kubernetes

About iunera

This Druid MCP Server is developed and maintained by iunera, a leading provider of advanced AI and data analytics solutions.

iunera specializes in:

  • AI-Powered Analytics: Cutting-edge artificial intelligence solutions for data analysis

  • Enterprise Data Platforms: Scalable data infrastructure and analytics platforms (Druid, Flink, Kubernetes, Kafka, Spring)

  • Model Context Protocol (MCP) Solutions: Advanced MCP server implementations for various data systems

  • Custom AI Development: Tailored AI solutions for enterprise needs

As veterans in Apache Druid iunera deployed and maintained a large number of solutions based on Apache Druid in productive enterprise grade scenarios.

For more information about our services and solutions, visit www.iunera.com.

Contact & Support

Need help? Let

  • Website: https://www.iunera.com

  • Professional Services: Contact us through www.iunera.com or email for enterprise support and custom development

  • Open Source: This project is open source and community contributions are welcome

© 2024

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Natural Language Analytics MCP server for Apache Druid. With this enterprise ready server in Java, one can query Apache Druid by natural language queries. Furthermore, the complete management like data loading of the Time Series Database Druid can be done with natural language commands.

  1. Overview
    1. Video Walkthrough
      1. Features
        1. Architecture & Organization
        2. MCP Inspector Interface
      2. Quick Start
        1. MCP Configuration for LLMs
        2. Prerequisites
        3. Build and Run
      3. Installation from Maven Central
        1. Prerequisites
        2. Download and Run
      4. For Developers
        1. Available Tools by Feature
          1. Data Management
          2. Ingestion Management
          3. Monitoring & Health
        2. Available Resources by Feature
          1. Available Prompts by Feature
            1. Environment Variables Configuration
            2. SSL-Encrypted Cluster with Authentication
          2. MCP Prompt Customization
            1. Prompt Configuration Structure
            2. Overriding Prompts
            3. Available Prompt Variables
            4. Prompt Template Examples
            5. Disabling Specific Prompts
          3. MCP Integration
            1. Transport Modes
            2. Read-only Mode
            3. What changes in read-only mode?
            4. 🐳 Druid Cluster Setup
            5. 🔧 Druid Cluster Configuration
            6. 📊 Code Ingestion Druid Extension
            7. Why Use These Together?
          4. Roadmap
            1. About iunera
              1. Contact & Support

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