mcp-confluent

An MCP server implementation that enables AI assistants to interact with Confluent Cloud REST APIs. This server allows AI tools like Claude Desktop and Goose CLI to manage Kafka topics, connectors, and Flink SQL statements through natural language interactions.

<a href="https://glama.ai/mcp/servers/@confluentinc/mcp-confluent"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@confluentinc/mcp-confluent/badge" alt="mcp-confluent MCP server" /> </a>

Demo

Goose CLI

Claude Desktop

Table of Contents

• mcp-confluent
  • Demo
    • Goose CLI
    • Claude Desktop
  • Table of Contents
  • User Guide
    • Getting Started
    • Configuration
      • Prerequisites & Setup for Tableflow Commands
    • Authentication for HTTP/SSE Transports
    • Environment Variables Reference
    • Usage
    • Configuring Claude Desktop
    • Configuring Goose CLI
    • Configuring Gemini CLI
    • mcp-confluent CLI Usage
      • Basic Usage
      • Example: Deploy using all transports
      • Example: Allow Only Specific Tools
      • Example: Block Certain Tools
      • Example: Use Tool Lists from Files
      • Example: List All Available Tools
  • Flink Catalog and Diagnostics
    • Flink Tools
    • Example Workflows
  • Developer Guide
    • Project Structure
    • Building and Running
    • Docker
      • Prerequisites
        • Environment Variables
      • Building and Running with Docker
      • Building and Running with Docker Compose
    • Testing
      • MCP Inspector
    • Adding a New Tool
    • Generating Types
    • Contributing

User Guide

Getting Started

1. Create a .env file: Copy the provided .env.example file to .env in the root of your project:

   cp .env.example .env
   

2. Populate the .env file: Fill in the necessary values for your Confluent Cloud environment. See the Configuration section for details on each variable.

3. Install Node.js (if not already installed)

   • We recommend using NVM (Node Version Manager) to manage Node.js versions
   • Install and use Node.js:

   nvm install 22
   nvm use 22
   

Configuration

Copy .env.example to .env in the root directory and fill in your values. See the example structure below:

<details> <summary>Example .env file structure</summary>

# .env file
BOOTSTRAP_SERVERS="pkc-v12gj.us-east4.gcp.confluent.cloud:9092"
KAFKA_API_KEY="..."
KAFKA_API_SECRET="..."
KAFKA_REST_ENDPOINT="https://pkc-v12gj.us-east4.gcp.confluent.cloud:443"
KAFKA_CLUSTER_ID=""
KAFKA_ENV_ID="env-..."
FLINK_ENV_ID="env-..."
FLINK_ORG_ID=""
FLINK_REST_ENDPOINT="https://flink.us-east4.gcp.confluent.cloud"
FLINK_ENV_NAME=""
FLINK_DATABASE_NAME=""
FLINK_API_KEY=""
FLINK_API_SECRET=""
FLINK_COMPUTE_POOL_ID="lfcp-..."
TABLEFLOW_API_KEY=""
TABLEFLOW_API_SECRET=""
CONFLUENT_CLOUD_API_KEY=""
CONFLUENT_CLOUD_API_SECRET=""
CONFLUENT_CLOUD_REST_ENDPOINT="https://api.confluent.cloud"
SCHEMA_REGISTRY_API_KEY="..."
SCHEMA_REGISTRY_API_SECRET="..."
SCHEMA_REGISTRY_ENDPOINT="https://psrc-zv01y.northamerica-northeast2.gcp.confluent.cloud"

</details>

Prerequisites & Setup for Tableflow Commands

In order to leverage Tableflow commands to interact with your data ecosystem and successfully execute these Tableflow commands and manage resources (e.g., interacting with data storage like AWS S3 and metadata catalogs like AWS Glue), certain IAM (Identity and Access Management) permissions and configurations are essential.

It is crucial to set up the necessary roles and policies in your cloud environment (e.g., AWS) and link them correctly within Confluent Cloud. This ensures your Flink SQL cluster, which powers Tableflow, has the required authorization to perform operations on your behalf.

Please refer to the following Confluent Cloud documentation for detailed instructions on setting up these permissions and integrating with custom storage and Glue:

• Confluent Cloud Tableflow Quick Start with Custom Storage & Glue: https://docs.confluent.io/cloud/current/topics/tableflow/get-started/quick-start-custom-storage-glue.html

Ensuring these prerequisites are met will prevent authorization errors when the mcp-server attempts to provision or manage Tableflow-enabled tables.

Authentication for HTTP/SSE Transports

When using HTTP or SSE transports, the MCP server requires API key authentication to prevent unauthorized access and protect against DNS rebinding attacks. This is enabled by default.

Generating an API Key

Generate a secure API key using the built-in utility:

npx @confluentinc/mcp-confluent --generate-key

This will output a 64-character key generated using secure cryptography:

Generated MCP API Key:
================================================================
a1b2c3d4e5f6...your-64-char-key-here...
================================================================

Configuring Authentication

Add the generated key to your .env file:

# MCP Server Authentication (required for HTTP/SSE transports)
MCP_API_KEY=your-generated-64-char-key-here

Making Authenticated Requests

Include the API key in the cflt-mcp-api-Key header for all HTTP/SSE requests:

curl -H "cflt-mcp-api-Key: your-api-key" http://localhost:8080/mcp

DNS Rebinding Protection

The server includes additional protections against DNS rebinding attacks:

• Host Header Validation: Only requests with allowed Host headers are accepted

Configure allowed hosts if needed:

# Allow additional hosts (comma-separated)
MCP_ALLOWED_HOSTS=localhost,127.0.0.1,myhost.local

Additional security to prevent internet exposure of MCP server

• Localhost Binding: Server binds to 127.0.0.1 by default (not 0.0.0.0)

Disabling Authentication (Development Only)

For local development, you can disable authentication:

# Via CLI flag
npx @confluentinc/mcp-confluent -e .env --transport http --disable-auth

# Or via environment variable
MCP_AUTH_DISABLED=true

Warning: Never disable authentication in production or when the server is network-accessible.

Environment Variables Reference

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