MarketMirror

Name: MarketMirror
Author: DarkWorldCoder

by DarkWorldCoderversion 0.4.2i★ –iRuns on your computer

Registry nameio.github.DarkWorldCoder/market-mirror

Install

Overview

Description from the maker (original English)

Test ads, prices and sales pitches on simulated buyers; get a go / iterate / no-go report.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Marketing & social media

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "market-mirror": {
      "command": "uvx",
      "args": [
        "marketmirror"
      ]
    }
  }
}

Run this in your terminal

claude mcp add market-mirror -- uvx marketmirror

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "market-mirror": {
      "command": "uvx",
      "args": [
        "marketmirror"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "market-mirror": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "marketmirror"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account DarkWorldCoder, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Marketing & social mediai

More stars than 0% of the other 2966 servers in this category
Published to the registry more recently than 74% of the other 2966 servers in this category
Basic checks equal to or better than 100% of the other 2966 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MarketMirror safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.4.2) reached the registry 11 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

MarketMirror: AI Market Research & Marketing Simulation

Try your ads, prices, and sales pitch with simulated buyers before spending on a real campaign.

English · 简体中文

Open source and built for AI agents. Interviewed LLM buyer personas scroll simulated ad feeds, argue in an OASIS social simulation, answer a survey and hear your sales pitch. Ask in plain words (*"test these three ads on young parents in India"*) from Claude Code, Codex, Gemini CLI, Cursor or any MCP client, and get a go / iterate / no-go report in one offline HTML dashboard. Self-hosted: only the model calls (to the provider you choose) and optional public research leave your computer.

Built on MiroFish and CAMEL-AI's OASIS · listed in the official MCP Registry as io.github.DarkWorldCoder/market-mirror

[Open the live demo](https://darkworldcoder.github.io/market-mirror/demo/): the full dashboard from a 2,999-buyer simulated run, in your browser, no install. (Fitloop is an invented app; every number is simulated.)

Try it (Linux, macOS or WSL; needs Git, uv and Python 3.12):

git clone https://github.com/DarkWorldCoder/market-mirror.git && cd market-mirror

bash install.sh --configure # installs the engine, then asks which model provider to use ./mm start && ./mm cli quickstart --out scenarios/acme # 9 questions; prepares a small simulated market, then stops for review

The last line already makes model calls on the provider you chose, so start with a small market. If you chose a Claude Code or Codex login, run ./mm gateway start claude (or codex) before it. Already in an MCP client? Add the server with claude mcp add market-mirror -- uvx marketmirror (any client: command uvx, args ["marketmirror"]), then ask your agent to run doctor and setup. Full quick start.

If MarketMirror saves you one bad launch, a ⭐ helps other people find it. To hear about new tests and releases, use Watch → Custom → Releases.

▶ Watch the 60-second launch film (with captions) · vertical 9:16 cut · made with HyperFrames from launch-video/

Meet the buyers · What you can test · Screenshots · How it works · Example results · Evidence and limits · Get started · Documentation

What is MarketMirror?

MarketMirror gives you a practice audience for your next marketing decision. Describe your product and the people you want to reach. It creates AI-generated people who can react to your ads, compare prices, ask questions, raise concerns, and respond to a sales pitch.

You get a report explaining what interested them, what put them off, what to change, and what to test with real customers next. You can also watch the simulation and explore the results in a dashboard.

For example: you are launching a fitness app. Should the ad lead with “15 minutes a day” or “less than one gym visit”? Should the free trial ask for a payment card? MarketMirror lets you rehearse those choices before a live campaign.

The buyers are simulated. Their responses are generated by AI, so use them to develop and compare ideas. Confirm promising findings with real customers and small live experiments.

Who is it for?

If you are…	Use MarketMirror to…
A founder or small business owner	Explore how different people might understand your product, price, or launch offer.
A marketer or agency	Compare ads, headlines, emails, and audiences before choosing a live test.
A sales team	Practice a pitch, discover likely concerns, and try clearer answers.
A product or research team	Explore buying decisions and website journeys, then plan customer research.
A developer or AI agent builder	Run the same workflows through commands, an API, a Python library, or connected AI assistants.

Meet the simulated buyers

A simulated buyer is an AI-generated character representing someone in your intended audience. The character has a background and practical reasons for accepting, questioning, or rejecting an offer.

You choose the groups you want to explore—for example, students, working parents, and young professionals in selected countries. MarketMirror creates different people within those groups and can ask them about their lives before showing them your marketing.

What a buyer can have	Why it matters in a test
A background	Age, location, work, and life stage provide context for their response.
A budget and priorities	An offer may interest them but still compete with more urgent expenses.
A phone and internet connection	A heavy page or video may be inconvenient on their device or data plan.
People they consult	A partner, family member, or community may influence a purchase.
Trust concerns	Hidden fees, unclear claims, or a previous bad experience may make them hesitate.
A buying decision card	A summary records what could persuade them, what could stop them, and who else matters.

An illustrative buyer: a busy parent who wants short home workouts, uses a budget phone, and worries about surprise charges. They might like a low monthly price but reject a “free” trial that immediately asks for a payment card. Another buyer may care more about workout quality than price. These are invented examples, not findings from real customers.

In tests within the same run, buyers can remember earlier experiences. Someone who disliked an ad can carry that reaction into a later survey or pitch. Separate comparison scenarios keep their own histories.

Detailed characters help you explore different viewpoints. They do not make the generated answers representative of a real population.

What you can test

Your question	What MarketMirror does	What you can learn from the simulation
Which ad gets attention?	Places your ads among ordinary posts in simulated Facebook, Instagram, Reddit, TikTok, LinkedIn, or X feeds.	Which ads buyers stop at, ignore, click, comment on, or hide.
Which headline or message is clearer?	Shows different versions to different buyers and asks for their reactions.	Which wording draws interest and which creates confusion.
Does the price or offer feel right?	Asks price questions and compares offers or pricing tiers.	Where price becomes a concern and which terms need explaining.
What might happen around a launch?	Lets buyers post, reply, and react in a simulated social conversation with scheduled brand posts and events.	Questions, objections, and themes that emerge in the discussion.
Will an email interest them?	Tests subject lines, email content, or a sequence in simulated inboxes.	Generated opening, reading, and response choices. No emails are sent.
How does our sales pitch land?	Presents the pitch, collects concerns, tries your answers, and asks again.	Which concerns persist and whether your response helps or makes things worse.
Where does our website lose people?	Sends simulated visitors through a real website and records their actions.	Where they hesitate, leave, or complete a checked task such as adding to cart.
Which audience should we investigate first?	Compares responses across the groups and countries you selected.	Differences worth following up with real customer research.
What should we test next?	Uses the run and, when supplied, real campaign exports to suggest follow-up experiments.	A practical starting point for the next live test.
Do the simulations match our results?	Compares paired simulated and observed outcomes.	How well the simulation held up on those experiments and where it needs adjustment.

You can repeat a comparison to see whether its result changes between runs. You can also use different AI providers and inspect where they disagree. Both help reveal uncertainty within the simulation.

The process at a glance

Describe your product. Provide a brief, documents, or a website: what you sell, who it helps, what it costs, and what supports your claims. You can also bring linked public feedback or campaign exports.
Choose your audience. Describe the groups and locations you want to explore. MarketMirror creates the simulated people. Review their profiles befo

Only the beginning is shown; read the rest in the repo

MarketMirror

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Marketing & social mediai

Common questions

Alternatives

MCP YouTube Transcript

Google Analytics MCP

BibiGPT YouTube Video Summarizer

README from the maker

MarketMirror: AI Market Research & Marketing Simulation

What is MarketMirror?

Who is it for?

Meet the simulated buyers

What you can test

The process at a glance