{"id":"cefboud-kafka-mcp-server","name":"kafka-mcp-server","af_score":46.5,"security_score":29.5,"reliability_score":17.5,"what_it_does":"Kafka MCP Server is a Model Context Protocol (MCP) server that lets an LLM client interact with an Apache Kafka cluster using natural-language tool calls. It provides MCP tools to inspect Kafka (e.g., topics, consumer groups/lags, broker/controller info, offsets) and to operate on topics (e.g., produce messages, create topics, consume messages). It can be run locally via Docker or as a Go binary, and supports an optional “MultiplexTool” mode to batch multiple tool calls in a single request (with optional Gemini-backed PROMPT_ARGUMENT inference).","best_when":"You have a Kafka cluster reachable from the host running the MCP server (or via Docker networking), and you want an LLM-driven ops/debug workflow around topic metadata, offsets, consumer-group lag, and message production/consumption.","avoid_when":"You cannot safely expose the MCP server to trusted clients only; you require TLS/authentication between the MCP client and server; or you need features explicitly not listed as available (consumer group offset reset, Kafka Connect, Schema Registry).","last_evaluated":"2026-04-04T19:45:31.347966+00:00","has_mcp":true,"has_api":false,"auth_methods":["None described for MCP server; configuration is via environment variables/CLI flags (e.g., KAFKA_MCP_BOOTSTRAP_SERVERS).","Optional Gemini API key for PROMPT_ARGUMENT inference when using MultiplexTool (GEMINI_API_KEY)."],"has_free_tier":false,"known_gotchas":["Some tools are marked as not implemented (e.g., consumer group offset reset, Kafka Connect, Schema Registry).","Message consumption/production actions can be stateful and may have side effects; agents should respect --read-only when appropriate.","Multiplexing’s PROMPT_ARGUMENT inference depends on Gemini and requires GEMINI_API_KEY; mis-inferred arguments can lead to incorrect tool inputs.","No explicit rate-limit guidance is provided; agent callers may need to manage request pacing themselves."],"error_quality":0.0}