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DimensionCodescene MCP ServerExpose CodeScene's Code Health analysis as local AI-friendly tools.NPM Sentinel MCP ServerAI-powered NPM package analysis MCP server
FMRS46 / 100 · D79 / 100 · B
Reliability7 / 2012 / 20
Security and permissions8 / 2016 / 20
Maintenance6 / 2018 / 20
Documentation13 / 2018 / 20
Setup experience12 / 2015 / 20
Best for
  • Teams integrating AI-driven development with code quality analysis
  • Developers aiming to safely refactor legacy code with AI assistance
  • Organizations embedding code health checks in CI/CD pipelines
  • Developers auditing NPM dependencies within AI workflows
  • Teams performing supply chain security assessments
  • Users of Claude Desktop, Cursor, or VS Code
Not for
  • Users without a CodeScene account or standalone license (though a standalone Code Health MCP is available)
  • Scenarios requiring zero network dependency after setup (analysis is local but fetches data from CodeScene)
  • Teams needing a complete replacement for CodeScene's platform features
  • Projects outside the NPM ecosystem (e.g., pure Python/Go)
  • Environments without network access to deps.dev, OSV.dev, and the npm registry
  • Scenarios requiring maintenance by an official upstream vendor
Required permissions
  • Requires CS_ACCESS_TOKEN to fetch data from a CodeScene instance
  • Read access to the local codebase for analysis
  • Volume mount for Docker installations to access code
  • Environment variables for custom SSL certificates (e.g., REQUESTS_CA_BUNDLE)
  • Can set CS_DISABLE_VERSION_CHECK to disable version checks
  • Network access to the NPM registry and external services (deps.dev, OSV.dev, OpenSSF, npms.io, GitHub)
  • Read access to workspace lockfiles (pnpm-lock.yaml, package-lock., yarn.lock) for cache invalidation
Risks and side effects
  • Transmission risk: Analysis results are fetched via REST from your own CodeScene account; source code is not sent externally, but token security is critical.
  • Dependency risk: A valid access token is required; token leakage could expose data.
  • Model limitations: Older models may not adhere to MCP constraints, affecting refactoring quality.
  • Path hallucination: IntelliJ's AI assistant may provide incorrect MCP paths, causing connection issues.
  • Third-party READMEs and changelogs are untrusted external content; they are wrapped in tags with _meta flags but should still be handled cautiously
  • Depends on availability and accuracy of external services
  • Batch requests are capped at 25 packages to prevent registry enumeration; larger sets require batching
  • Third-party open source project, not officially maintained by NPM or Anthropic
Supported clientsClaude Desktop, VS Code, JetBrains IntelliJ, GitHub Copilot, CursorClaude Desktop, VS Code, Cursor
Tools519