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Alternatives to dockerlint-mcp

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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables an AI to statically lint Dockerfiles and compose files without Docker by parsing their true structure, reporting line-numbered findings with concrete fixes, and analyzing cache order, .dockerignore matching, and safe fix previews as diffs.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Exposes a Dockerfile auditing engine to AI assistants, letting them scan a Dockerfile for the 32 deterministic layer-aware rules, print a stage/layer map showing what each layer adds or deletes, explain any rule's rationale and fix, and list available rules. Findings include file:line evidence so agents can surface and triage image-safety issues directly in Claude Code, Cursor, or Cline.
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables agents to validate Dockerfiles for build-breaking syntax errors, risky patterns like root users and secrets in ENV/ARG, and cache-order problems, returning every finding with its line and a fix. It also verifies referenced container images against public registries, reporting tag existence, digests to pin, supported platforms, last rebuild time, and end-of-life status with an upgrade tag.
      2
      1
      MIT
    • A
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables AI assistants to interact with Docker containers through safe, permission-controlled access to inspect, manage, and diagnose containers, images, and compose services with built-in timeouts and AI-powered analysis.
      -
    • A
      license
      A
      quality
      A
      maintenance
      Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.
      16
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables users to analyze Dockerfiles without a Docker daemon or build, ranking layer sizes biggest first and surfacing deterministic waste flags. It also validates supplied layer sizes against the number of layer-producing instructions.
      MIT

    TDQS

    A3.9/5.0

    Scored across 7 tools

    Disambiguation4/5

    Each tool has a fairly distinct role: overview summarizes, lint_dockerfile reports rule findings, explain_layers focuses on layer/cache heuristics, fix_preview shows diffs. There is minor overlap between explain_layers' order/cache problems and lint_dockerfile's cache-busting rule, but descriptions clarify the split.

    Naming Consistency4/5

    All tools use snake_case, which is consistent, but the ordering is mostly verb_noun (lint_dockerfile, check_dockerignore, fix_preview) with one noun_verb outlier (dockerfile_overview). Readable and predictable overall with a single minor deviation.

    Tool Count5/5

    Seven tools is well-scoped for a Dockerfile/compose linting server, each covering a distinct artifact (Dockerfile, compose, dockerignore) or function (summarize, lint, explain, suggest, fix). No tool feels redundant or like padding.

    Completeness4/5

    The surface covers the full lint lifecycle for Dockerfiles plus compose and .dockerignore, with suggestions and fix previews but no write/apply by design. Minor gaps exist, such as no automatic fix suggestions for compose or dockerignore, but core workflows are covered.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues