mcp-kafka serves as a powerful server facilitating interactions between AI assistants and Apache Kafka clusters. By leveraging the Model Context Protocol, it enables seamless operations such as topic creation, message production, and consumption. This tool simplifies the integration of AI with Kafka, enhancing productivity and innovation.
mcp-kafka is an innovative Model Context Protocol (MCP) server designed to facilitate Kafka client operations through AI assistants. This project serves as a comprehensive bridge between AI assistants and Apache Kafka, enabling seamless interactions with Kafka clusters via the Model Context Protocol. With mcp-kafka, AI assistants can effortlessly create, manage, and interact with Kafka topics and messages, streamlining operations and enhancing productivity.
Key Features
mcp-kafka provides an array of essential Kafka operations, including:
- Create Topic: Efficiently create new Kafka topics with customizable partitions and replication factors.
- List Topics: Retrieve a comprehensive list of all available Kafka topics within the cluster.
- Delete Topic: Remove existing Kafka topics as needed.
- Describe Topic: Access detailed information about specific topics, including partition details for better management.
- Produce Message: Send messages to a Kafka topic with support for both message keys and headers, enhancing message organization and retrieval.
- Consume Messages: Read from Kafka topics with configurable timeout settings to optimize message consumption.
Configuration Parameters
The mcp-kafka tool is equipped to handle various configuration parameters, allowing users to tailor their interactions:
| Parameter | Description | Default |
|---|---|---|
| topic | Topic to interact with | (required) |
| num_partitions | Number of partitions for topic creation | (optional) |
| replication_factor | Replication factor for topic creation | (optional) |
| produce_message_key | Key for produced messages | (optional) |
| produce_message_value | Value for produced messages | (optional) |
| produce_message_headers | Headers for produced messages | (optional) |
| consumer_timeout | Timeout in seconds for message consumption | 10 |
These parameters can be naturally derived from user messages in real-time, making the tool user-friendly and efficient.
For those interested in seeing the tool in action, a short video demonstration is available.
Contributing
Contributions to mcp-kafka are highly encouraged. Developers can submit Pull Requests to improve the project and its functionalities. To understand more about its usage and configuration, users can refer to the documentation provided within the repository.
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