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Add architectural guardrails for AI-written code with analysis and CI checks.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "ovecc" MCP server from askskill: Run: claude mcp add 'io-github-ovecc-labs-ovecc' -- npx -y ovecc
Developers can use it when AI generates or edits code to inspect dependencies and architectural boundaries, reducing the risk of unhealthy coupling.
Teams can analyze which modules a change may affect before committing or opening a merge request, helping surface high-impact changes early.
DevOps or engineering teams can integrate dependency checks, dead code detection, and architectural gates into CI as part of automated quality control.
It is an architectural guardrail tool for AI-written code, focused on dependency graphs, impact analysis, dead code detection, and CI gates.
Yes. The original description explicitly mentions a CI gate, which indicates it can be used for architecture or quality gate checks in CI workflows.
The provided material does not include installation steps, runtime requirements, or API key details. See the source repository for specifics.
Group AI-generated code changes into reviewable commit candidates before approval.
Query live architecture models, fetch target patterns, and check files for compliance.
Establish enterprise governance, delivery standards, and assurance for AI coding assistants.
Validate AI-generated code against real codebases before bugs reach runtime.
Scan AI-generated code for injections, secrets, SSRF, and risky patterns.
Automatically save and restore AI sessions to preserve architecture context and decisions.