agentic-engineering-for-apache-kafka — security grade SAFE, quality 72/100

Security audit verdict: SAFE · quality 72/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by lensesio · MCP Server · ★ 56

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

🔒 Is agentic-engineering-for-apache-kafka safe to install? View the security audit →

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 exploration or investigation. Maintained by Lenses.io, the team that pioneered the developer experience for Apache Kafka. Agentic engineering has shifted what that means. Making sure an AI agent knows how to handle streaming data is now part of the job. Why Skills and MCP? A Kafka MCP server gives agents access to your live cluster: topics, consumer groups, connectors, schemas and metrics. The skills in this repository teach agents expertise: best practices, audit thresholds, remediation playbooks and standard workflows. Together they enable AI-powered Kafka engineering where the agent doesn't just read your cluster, it knows what to look for and h

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

Quick Facts

Stars56
Forks16
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score72.4716355555101/100
Open Issues1
Last Updated2026-08-21
Created2026-01-26
Platformsclaude-code, mcp, python
Est. Tokens~16k

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%)

agentic-engineering-for-apache-kafka alternative? Top 6 similar tools

Looking for a agentic-engineering-for-apache-kafka alternative? If you're comparing agentic-engineering-for-apache-kafka with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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Frequently Asked Questions

What is agentic-engineering-for-apache-kafka?

agentic-engineering-for-apache-kafka is AI agent skills for building, operating and troubleshooting Apache Kafka applications. Topic audit, consumer lag, schema review, security, connectors and DLQ. It is categorized as a MCP Server with 56 GitHub stars.

What programming language is agentic-engineering-for-apache-kafka written in?

agentic-engineering-for-apache-kafka is primarily written in Python. It covers topics such as agent-skills, agentic-engineering, apache-kafka.

How do I install or use agentic-engineering-for-apache-kafka?

You can find installation instructions and usage details in the agentic-engineering-for-apache-kafka GitHub repository at github.com/lensesio/agentic-engineering-for-apache-kafka. The project has 56 stars and 16 forks, indicating an active community.

What license does agentic-engineering-for-apache-kafka use?

agentic-engineering-for-apache-kafka is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to agentic-engineering-for-apache-kafka?

The top alternatives to agentic-engineering-for-apache-kafka on Agent Skills Hub include awesome-ai-agent-skills, awesome-agentic-devops, ox. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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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