Bangermap

Name: Bangermap
Author: AdesiaHQ

by AdesiaHQversion 1.0.3i★ –iRuns on your computer

Registry nameio.github.AdesiaHQ/bangermap-mcp

Install

Overview

Description from the maker (original English)

Find YouTube outliers, videos that beat their channel's own baseline, on your own free API key.

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
You need to fill in: YOUTUBE_API_KEY

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).
You fill in yourself: YOUTUBE_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx 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": {
    "bangermap": {
      "command": "npx",
      "args": [
        "-y",
        "bangermap-mcp"
      ],
      "env": {
        "YOUTUBE_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add bangermap --env YOUTUBE_API_KEY=your-value -- npx -y bangermap-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "bangermap": {
      "command": "npx",
      "args": [
        "-y",
        "bangermap-mcp"
      ],
      "env": {
        "YOUTUBE_API_KEY": "your-value"
      }
    }
  }
}

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": {
    "bangermap": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "bangermap-mcp"
      ],
      "env": {
        "YOUTUBE_API_KEY": "your-value"
      }
    }
  }
}

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.

Values you fill in

YOUTUBE_API_KEY secret required env
Your own YouTube Data API v3 key, created free in the Google Cloud console

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 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account AdesiaHQ, 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 2987 servers in this category
Published to the registry more recently than 23% of the other 2987 servers in this category
Basic checks equal to or better than 100% of the other 2987 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 Bangermap 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?

You need to fill in: YOUTUBE_API_KEY

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 (1.0.3) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

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

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

MCP YouTube Transcript

by jkawamoto

An MCP server retrieving transcripts of YouTube videos

Runs on your computer★ 495MITUpdated 10 days ago

Install

Google Analytics MCP

by surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

Runs on your computer★ 244MITUpdated 10 days ago

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BibiGPT YouTube Video Summarizer

by JimmyLv

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

Runs in the cloud★ 137MITUpdated 10 days ago

Install

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.

bangermap-mcp

YouTube outlier research over MCP, running on your own free YouTube Data API key.

An outlier is a video that beat its own channel's normal performance. A 10x on a small channel is a stronger signal than a million views on a channel that always gets a million, because it is proof an idea worked without an audience behind it. This server measures that, from any MCP client.

No account, no credits, no meter. The data comes from Google's public API on your key, so the only quota is the free 10,000 units a day Google already gives you, which is roughly 1,100 channel scans.

Setup

Create a free key in the Google Cloud console, enable YouTube Data API v3 on its project, then point your client at the server.

Claude Code:

claude mcp add bangermap --env YOUTUBE_API_KEY=your-key -- npx -y bangermap-mcp

Claude Desktop, in claude_desktop_config.json:

"mcpServers": { "bangermap": { "command": "npx", "args": ["-y", "bangermap-mcp"], "env": { "YOUTUBE_API_KEY": "your-key" } } } }

Any other MCP client works the same way. The server speaks stdio and needs only YOUTUBE_API_KEY in its environment.

Tools

Tool	What it answers	Cost
`find_outliers`	Which of this channel's recent uploads beat its own baseline, and by how much	~5 units
`channel_baseline`	What normal looks like for this channel, so a view count can be judged	~5 units
`compare_channels`	What is working across a set of competitors, each measured against itself	~5 units per channel
`sweep_niche`	Which channels a seed channel is connected to, and what is overperforming on them	~5 units per channel

Channels can be given as a URL, an @handle, a channel id, or the URL of any video on the channel.

Discovery runs through the channel graph rather than keyword search on purpose. Google caps search at 100 calls a day on a free key while channel reads cost a single unit, so seeding from a channel you already know is both cheaper and deeper.

How the baseline works

For each channel, the baseline is the median views of its recent uploads of the same format, counting only uploads old enough to have settled. Shorts and long-form get separate baselines, since comparing a 40-second Short against a 20-minute upload would flatter one and punish the other. A video's multiple is its views divided by that baseline.

The outlier multiple and the baseline are computed by this server, not by YouTube. View and channel data comes from the YouTube Data API. YouTube is a trademark of Google LLC.

The app

This server shares its scoring engine with Bangermap, a Mac app for the same research when you want it to persist. The app keeps a watchlist that re-scans and flags what is new since your last visit, shows outliers in a thumbnail wall for pattern study, exports to CSV, and caches locally so repeat research does not re-spend quota. One payment, no subscription, same free key.

There is also a free browser version at bangermap.com/tools/outlier-finder if you want to try the measurement without installing anything, and an n8n community node, n8n-nodes-bangermap, for the same operations inside a workflow.

Bangermap

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

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

bangermap-mcp

Setup

Tools

How the baseline works

The app