agentic-engineering-for-apache-kafka: AI agent skills for building, operating and troubleshooting Apache Kafka applications

by lensesio · MCP Server · ★ 56

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install agentic-engineering-for-apache-kafka

/plugin marketplace add lensesio/agentic-engineering-for-apache-kafka
npx skills add lensesio/agentic-engineering-for-apache-kafka

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 72/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsagentic-engineeringapache-kafkaclaude-codecontext-engineeringcursordata-engineeringdevopskafkakafka-connect

Quick Facts

Stars56
Forks16
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score72/100
Open Issues1
Last Updated2026-08-21
Created2026-01-26
Platformsclaude-code, mcp, python
Est. Tokens~16k

About agentic-engineering-for-apache-kafka

🌊 Agentic Engineering for Apache Kafka A collection of agent skills that turn AI agents and coding tools such as Claude Code and Cursor into Kafka-specialised engineering assistants. Audit topic configurations, diagnose consumer lag, review schema changes, review connectors and DLQs, catch security misconfigurations and tune performance, all from a single prompt instead of 15 minutes of manual...

Compatible Skills

These tools work well together with agentic-engineering-for-apache-kafka for enhanced workflows:

  • agent-skills — semantic(0.51)+complementary+rare_topics+same_lang+similar_pop+shared_platform (67%)
  • skills — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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