Apache Kafka is an open-source distributed event streaming platform used for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.
Provides monitoring and management for Apache Kafka clusters, including cluster/topic metadata, consumer groups and lag, topic creation and configuration, partition management, offset resets, and guarded deletion of topics and consumer groups.
Enables MCP-capable clients to monitor and manage Apache Kafka clusters, including topics, partitions, configs, and consumer groups with lag, while enforcing configurable security modes, topic allowlists, protected topics, and audit logging.
6
74 npm
1
MIT
Why this server?
Allows AI assistants to interact with Apache Kafka clusters via AKHQ's REST API, providing tools for managing topics, consumer groups, schema registry, nodes/brokers, Kafka Connect, ksqlDB, and ACLs.
Enables AI assistants to interact with Apache Kafka clusters through AKHQ's REST API. Supports multi-environment configuration, flexible authentication, and comprehensive coverage of topics, consumer groups, schema registry, Kafka Connect, ksqlDB, and ACLs.
58
10 npm
MIT
Why this server?
Enables AI agents to interact with Apache Kafka message clusters through the MCP protocol, allowing safe and efficient Kafka messaging operations.
Enables large language models and AI agents to securely and efficiently interact with Apache Kafka clusters through the Model Context Protocol.
11
65 PyPI
Apache 2.0
Why this server?
Provides tools for reading and searching Kafka messages through a Redpanda Console HTTP API, including listing topics, viewing cluster info, describing topic configurations, fetching messages by offset or timestamp, and searching message contents.
Enables AI assistants to read and search Kafka messages through the Redpanda Console HTTP API, including topic listing, message fetching by offset or time, and substring search, without direct Kafka broker access.
7
196 npm
1
MIT
Why this server?
Provides tools for managing Apache Kafka clusters, including listing and describing topics, consumer groups, cluster metadata, producing and consuming messages, creating and altering topics, and managing ACLs.
Reference implementation of KIP-1318, a secure Model Context Protocol server for Apache Kafka that enables AI agents to interact with Kafka clusters through governed tools and resources.
11
2
Apache 2.0
Why this server?
Provides integration with Apache Kafka through Lenses.io, enabling exploration, transformation, and joining of data in Kafka topics across multiple clusters using SQL queries without requiring an additional database.
Manage, explore, transform and join data in Kafka topics across multiple clusters using different flavours of Apache Kafka via Lenses.io (including the free Community Edition)
42
28
Apache 2.0
Why this server?
Connects to EventCatalog instances that document Kafka-based architectures, enabling queries about event schemas, producers, consumers, and message flows
A server that connects MCP clients (Claude, Cursor, Windsurf, etc.) to EventCatalog instances, allowing users to ask questions about their event-driven architecture and get insights about domains, services, and message schemas directly within their development tools.
214 npm
24
MIT
Why this server?
Provides tools for managing Kafka clusters, topics, users, ACLs, connectors, and more on Kubernetes via the Strimzi operator.
Manage Apache Kafka on Kubernetes via Strimzi. Clusters, topics, users, connectors, MirrorMaker2, and node pools.
92
Apache 2.0
Why this server?
Provides real-time observability into Apache Kafka clusters, enabling AI agents to monitor broker health, track consumer lag, and diagnose issues through natural language.
An MCP server that gives AI agents real-time observability into Apache Kafka clusters, enabling natural language queries for broker health, consumer lag, and diagnostics.
