Give your AI
    big data on games

    Install Mappex MCP so your AI agent knows how games are built and what players think about their individual decisions.

    Your agent will stop going by vibes and start working from real data.

    Connect Mappex MCP

    You

    Is the Mirror of Night in Hades good design? Assess it.

    ChatGPT Pro

    Weak evidence

    That is a thin source mix for a question on whether some system is good or not.

    No signal weight

    Although it may read some reviews, it cannot tell whether some feedback is actually dominant, niche, repeated, or contradicted. Even if you ask it to do so, it will only give you surface-level vibes, not real stats.

    Sounds smart, but...

    The model just infers possible positive effects from system description. Does not actually represent what players think.

    Prompt whiplash

    The model flips once corrected because it never knew a large feedback corpus. And because it still doesn't, you can't rely on it when making decisions.

    Searches the web

    Reads dev blog, IGN, whatever

    Doesn't count feedback

    Thought for 3 minutes

    Yes. The Mirror is strong because it turns failed runs into permanent progress and adds build variety.

    But people complain about progression

    Thought for 3.5 minutes

    You're absolutely right. It may be bad for some players.

      Deepseek 4 Flash + Mappex

      • ✓ Game found: Hades
      • ✓ Read Mirror of Night analysis
      • ✓ Checked player feedback on pacing and upgrades

      Not good design

      Progression pacing satisfaction is 22.9%
      2nd dash and other critical upgrades are locked behind grind, causing early-game complaints
      Late-game is trivialized before player gets to true ending
      Most upgrades are flat stat sticks - depth satisfaction is only 54.9%
      Story, satisfying combat, and optional difficulty make the rough system feel better than it is.
      If you want this in your game - make core combat verbs baseline and use upgrades for sidegrades.

      $200/mo

      10+ minutes wait

      Not a joke. See it yourself

      $16/mo

      Response in ~10 seconds

      "AI is bad at games"
      We get it.

      And we know why

      Generic models sound like good designers.
      It's not the same as knowing what actually works.

      Because of that, it takes a lot of expertise and vigilance to ask the right questions and see when it's getting things wrong.

      But then it's not an assistant - it's a rubber duck.

      The solution

      Data layer first.
      Assistant sits on top.

      01

      Map the target game

      Mappex gathers the actual game context first: mechanics, audience, positioning, references, and player feedback.

      02

      Extract what matters

      It separates noise from repeated praise, complaints, tensions, and design learnings: what works, what breaks, and why.

      03

      Evaluate every axis

      The pipeline reads thousands of reviews and evaluates the game across design, audience, content, usability, monetization, and market-fit axes.

      04

      Put chat on top

      The assistant answers from the Mappex data layer instead of synthesizing on the fly from arbitrary ranked sources.

      The model is not researching.

      The research is already done by a specialized analytical pipeline. The assistant just reads it.

      Integrate MCPRead MCP setup guide

      Don't have an AI assistant yet? Use Mappex Chat

      Use Mappex with any assistant.

      Connect Mappex MCP
      01

      Cursor

      02

      Claude Code

      03

      Codex

      04

      Windsurf

      05

      VS Code

      06

      Claude Desktop

      07

      ChatGPT apps

      08

      Chatwise

      + any other tool that supports MCP

      Bring Mappex to your agent

      Give any assistant the same game intelligence layer.

      Connect Mappex MCPUse Mappex Chat