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Verify code against YAML specs to catch schema drift before commits.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "spec-drift-mcp" yet — see the docs or source repo.
Check the user model implementation in the current branch against schema/api/user.yaml. List missing fields, extra fields, and type mismatches, then suggest fixes.
A diff report showing fields that diverge from the YAML spec, with recommended fixes.
Validate the current service configuration code against deploy/specs/service.yaml. Find naming mismatches, missing configs, and wrong data types, then rank them by severity.
A severity-ranked issue list describing where each drift occurs and its impact.
Validate implementations in src/models against specs/*.yaml and generate a CI-friendly summary: passed checks, failed checks, failure reasons, and suggested remediation steps.
A structured validation summary ready for CI logs or merge request comments.
Create, review, and manage specs for AI-driven coding and testing workflows.
Scan codebases for incompleteness and quantify LLM context drift risk.
Guides AI coding tools through spec-first development workflows and quality checks.
Understand codebases, detect conventions, and retain decisions across sessions.
Validate, convert, and lint YAML files with an AI-powered MCP tool.
Check documentation against source code and suggest fixes for drift.