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Alternatives to package-intel-mcp

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    Related Servers

    • A
      license
      A
      quality
      D
      maintenance
      Package intelligence for AI coding agents that checks npm and PyPI package health, deprecation, vulnerabilities, bundle size, and compares alternatives.
      5
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to vet npm and PyPI packages before installation, reporting typosquats, vulnerabilities in the selected version, publisher changes, and names that don't exist or were published within the last 30 days. It also exposes DNS, WHOIS, email, JWT and file/image utilities as tools over Streamable HTTP, with no signup or API key required.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to identify exactly what broke between two dependency versions, with citations for every claim, and to verify package existence to catch typosquatting, all without requiring an API key.
      MIT
    • A
      license
      Not graded
      quality
      F
      maintenance
      Open source intelligence for AI agents — GitHub project-health scoring, package dependency-risk analysis, trending repositories, license checks, and side-by-side package comparison.
      MIT

    TDQS

    A3.9/5.0

    Scored across 6 tools

    Disambiguation4/5

    Each tool targets a distinct aspect of package intelligence (downloads, metadata, versions, dependencies, health, search), so selection is generally clear. There is mild overlap between package_info and package_health, since health reports a superset of info fields like license and deprecation, but the composite/actionable framing of health distinguishes it.

    Naming Consistency5/5

    All six tools use a uniform package_<noun> snake_case pattern (package_info, package_versions, package_dependencies, etc.), making names highly predictable. No mixing of conventions or verb styles.

    Tool Count5/5

    Six tools is well-scoped for a package-intelligence server, with each tool earning its place across popularity, metadata, versions, dependencies, health, and search. Nothing feels redundant or missing in size.

    Completeness4/5

    The surface covers a full evaluation lifecycle: discover (search), inspect (info, versions), assess risk (downloads, dependencies, health). Minor gap: package_search only works for npm and cargo, and there is no reverse-dependency or license-compatibility operation, but core workflows are covered.

    Maintenance

    ActivityActive
    ResponsivenessNo issues