code-guardian
Related Servers
Alternatives to code-guardian
No user-submitted related servers found.
Related Servers
AlicenseNot gradedqualityNot gradedmaintenanceLocal repository health diagnosis and fix planning for AI-written JavaScript, TypeScript, Python and mixed projects. Its stdio MCP server exposes scans, finding explanations, repair plans, verification, privacy review and DPDP technical readiness checks.214 npm32GPL 3.0
repo-doctorofficial
AlicenseNot gradedqualityCmaintenanceMCP server that produces scored, evidence-cited audits of public GitHub repos via tools for fetching metadata, reading files, scanning git history, and checking hygiene.MIT- AlicenseAqualityAmaintenanceFree deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil2MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents and other MCP clients to interrogate a repository — or a frontend and backend pair — returning a single JSON document of findings such as which calls reach which routes, what is dead, and where to refactor first. Exposes tools like analyze_repo, cross_repo, check_endpoint, and check_coverage, along with contract resources for authoring adapters and rule packs, entirely over local stdio with no network access.MIT
- AlicenseAqualityCmaintenanceLocal-only GitHub Actions and CI maintenance scanner for AI-built apps. Exposes scan, explanation, and fix-planning tools to MCP clients; modifies nothing and makes no outbound requests by default.335 npm2MIT
- AlicenseNot gradedqualityCmaintenanceSecurity scanner for MCP servers and AI-generated code. Detects leaked API keys, PII, prompt injection, and MCP misconfigs with A-F security grades.MIT
TDQS
Scored across 3 tools
scan and orphans overlap since scan already reports 'orphan-code hygiene' while orphans drills into the same dead-code data, and explain is a wrapper that reruns scan. The descriptions do clarify the distinctions (drill-down vs. narrative), but boundaries are not fully crisp.
All three names are single lowercase words with a consistent style (scan, orphans, explain), which is readable and predictable. There is minor inconsistency in word class (two verbs vs. one noun) and no verb_noun pattern, but the convention is uniform enough.
Three tools is slightly thin but each earns its place: a primary scan, a focused drill-down, and an LLM summary mode. The surface fits the narrow, well-defined purpose of static safety scanning without redundancy.
For a parse-only safety/completeness scanner, the set covers the core workflow (assess safety, inspect dead code, get a plain-English explanation) with graceful degradation when no model is available. Minor gaps exist around configuration/dependency analysis, but core needs are met.