What features does Confluent MCP server provide?

Q: What features does Confluent MCP server provide?

Multi-transport MCP server: Supports HTTP, SSE, and STDIO transports; registers MCP routes and exposes server endpoints, with sample startup logs to indicate which transports are active.. Tool access control (allow/block): Configure allowed or blocked tools via command-line options or files; allow-list is applied before block-list, with a default of all tools enabled if neither is provided.. Rich Confluent Cloud toolset: Provides a broad set of tools for Kafka topics, topic config, connectors, Flink statements, and Tableflow resources (topic, catalog, and related operations). A comprehensive list of available tools is provided via the CLI.. Claude Desktop & Goose CLI integration: Guides to configure Claude Desktop and Goose CLI to run the MCP server from source or via npx, including environment-file usage and example configurations.. Gemini CLI integration: Demonstrates registering the mcp-confluent extension with Gemini CLI and using a local .env file for integration.. Docker & Docker Compose support: Includes Dockerfile and docker-compose workflow for building and running the MCP server, with port mapping and environment-variable configuration.. MCP CLI usage and examples: A feature-rich CLI (mcp-confluent) with options for environment files, transports, and tool filtering; includes example deployments and mode demonstrations.. Environment-driven configuration: Extensive .env configuration support with an Environment Variables Reference covering HTTP, SSE, REST endpoints, API keys, and Confluent Cloud/Tableflow settings.

Confluent MCP Server 2025: Features & Setup Guide

Overview

This MCP server, mcp-confluent, implements the Model Context Protocol (MCP) to enable AI assistants to interact with Confluent Cloud REST APIs. It exposes a configurable set of Confluent Cloud operations (topics, connectors, Flink SQL statements) via natural-language capable transports, allowing tools like Claude Desktop and Goose CLI to issue requests as if conversing with a human. The server can be started from source (with dependencies installed and a development workflow) or run directly via npx, and is designed to be paired with clients that specify the MCP server address and credentials. Transport options include HTTP, SSE, and STDIO, with a CLI to enable, disable, or constrain the available tools. It ships with a comprehensive environment-variable configuration model, including a detailed .env example and an Environment Variables Reference. The project supports Docker and Docker Compose for local development, as well as Gemini CLI and Claude Desktop integration, making it straightforward to deploy in a local or CI environment. A built-in CLI demonstrates deployment, tool listing, and filter capabilities, with demo assets for Goose CLI and Claude Desktop.

Features

Multi-transport MCP server

Supports HTTP, SSE, and STDIO transports; registers MCP routes and exposes server endpoints, with sample startup logs to indicate which transports are active.

Tool access control (allow/block)

Configure allowed or blocked tools via command-line options or files; allow-list is applied before block-list, with a default of all tools enabled if neither is provided.

Rich Confluent Cloud toolset

Provides a broad set of tools for Kafka topics, topic config, connectors, Flink statements, and Tableflow resources (topic, catalog, and related operations). A comprehensive list of available tools is provided via the CLI.

Claude Desktop & Goose CLI integration

Guides to configure Claude Desktop and Goose CLI to run the MCP server from source or via npx, including environment-file usage and example configurations.

Gemini CLI integration

Demonstrates registering the mcp-confluent extension with Gemini CLI and using a local .env file for integration.

Docker & Docker Compose support

Includes Dockerfile and docker-compose workflow for building and running the MCP server, with port mapping and environment-variable configuration.

MCP CLI usage and examples

A feature-rich CLI (mcp-confluent) with options for environment files, transports, and tool filtering; includes example deployments and mode demonstrations.

Environment-driven configuration

Extensive .env configuration support with an Environment Variables Reference covering HTTP, SSE, REST endpoints, API keys, and Confluent Cloud/Tableflow settings.