Gatekeeper FAQs

Question 1

What is Gatekeeper and what does it validate?

Accepted Answer

Gatekeeper is a comprehensive QA framework designed to validate Model Context Protocol (MCP) servers, Claude skills, and extensions. It ensures their quality, security, and conformance before publication through an 8-gate validation pipeline.

Question 2

What types of issues can Gatekeeper detect?

Accepted Answer

It detects a wide range of issues including schema violations, security vulnerabilities (like prompt injection, SSRF, SQL injection), functional bugs, and AI semantic mismatches between tool descriptions and actual behavior using LLM-powered evaluation.

Question 3

How does Gatekeeper use AI for semantic evaluation?

Accepted Answer

Gatekeeper's AI Semantic Gate (Gate 4) employs an LLM-as-judge (e.g., Claude) to assess description accuracy, parameter clarity, integration readiness, and tool chain coherence by comparing tool metadata against real invocation results.

Question 4

Can Gatekeeper be integrated into CI/CD workflows?

Accepted Answer

Yes, Gatekeeper generates detailed reports in multiple formats (JSON, HTML, SARIF) and offers a CLI, making it ideal for seamless integration into CI/CD pipelines like GitHub Actions for automated quality checks.

Question 5

What are the core validation gates in Gatekeeper?

Accepted Answer

Gatekeeper features 8 distinct gates: Schema, Security, Functional, AI Semantic, Human Review, Skills, Extensions, and Package validation, each addressing specific aspects of quality and conformance for the MCP ecosystem.

Gatekeeper

Gatekeeper

Key Features

Use Cases

Key Features

Use Cases