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DimensionCodescene MCP ServerExpose CodeScene's Code Health analysis as local AI-friendly tools.GitHub MCP ServerGitHub's official MCP server for managing repos, issues, PRs, and workflows via natural language
FMRS46 / 100 · D76 / 100 · B
Reliability7 / 2013 / 20
Security and permissions8 / 2014 / 20
Maintenance6 / 2018 / 20
Documentation13 / 2017 / 20
Setup experience12 / 2014 / 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
  • Teams that want an AI assistant to directly operate on GitHub repos and collaboration workflows
  • Users already in the GitHub Copilot ecosystem who want a zero-deployment remote option
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
  • Scenarios where you don't want the assistant to have write access to repos (enable only read-only toolsets)
  • Environments with strict network isolation for private repos that can't reach the official remote endpoint
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
  • A personal access token (PAT) or OAuth App token; effective scope depends on the token's own permissions
  • Enabling toolsets like actions/issues/pull_requests grants write access — request tokens on a least-privilege basis
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.
  • Write toolsets (creating/merging PRs, triggering workflows) can cause accidental changes if the token is overscoped — try a read-only toolset first
  • In hosted mode, credentials travel via the Authorization header — make sure the client-to-api.githubcopilot.com connection is trusted
Supported clientsClaude Desktop, VS Code, JetBrains IntelliJ, GitHub Copilot, CursorClaude Desktop, Claude Code, VS Code, Cursor, Windsurf, JetBrains IDEs, Zed, Amp
Tools515