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Alternatives to Mobile Game Fixer MCP

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.
      11 npm
      MIT
    • A
      license
      C
      quality
      B
      maintenance
      Enables an AI agent to auto-detect a game's engine (Unity, Unreal, Godot, Java, or native) from its files and then inspect, search, and patch the underlying binaries with in-process PE analysis, hex editing, pattern scanning, string extraction, checksums, diffing, and disassembly. Everything runs locally and offline with no cloud dependency or telemetry.
      10
      100
      22 npm
      5
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.
      12
      90 npm
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables any general-purpose agent to mod IL2CPP, Mono (.NET), and Unreal games by resolving hook targets from engine metadata rather than memory guessing. Provides 45 tools covering the full workflow of finding a game, indexing types/fields/methods, injecting a Frida probe, hooking methods, and reading or writing game memory.
      45
      MIT
    • A
      license
      B
      quality
      B
      maintenance
      Enables AI agents to run deterministic, fully local static security and compliance audits of code, configurations, and dependencies through 32 MCP tools covering 24 vulnerability categories. It also detects the project stack, generates risk reports and checklists, suggests stack-aware remediations, and re-validates fixes to confirm vulnerabilities were eliminated.
      32
      1
      MIT