Admob MCP Server

@ard3051997

代码仓库

基本信息

分类

开发工具

许可证

MIT

传输方式

stdio

作者

ard3051997

提交者

Abhishek Dhobe

关于 Admob MCP Server

MCP Server for Google AdMob — 14 tools for mediation management, revenue analysis, geo recommendations & A/B experiments via FastMCP

Admob MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "admob-mediation": {
      "command": "/path/to/MCP-admob/.venv/bin/python",
      "args": [
        "-m",
        "admob_mcp"
      ],
      "cwd": "/path/to/MCP-admob",
      "env": {
        "PYTHONPATH": "/path/to/MCP-admob",
        "PUBLISHER_ID": "pub-XXXXXXXXXXXXXXXX",
        "CREDENTIALS_PATH": "/path/to/MCP-admob/credentials.json",
        "TOKEN_PATH": "/path/to/MCP-admob/token.json",
        "AUDIT_LOG_PATH": "/path/to/MCP-admob/audit.log"
      }
    }
  }
}

Admob MCP Server 工具

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工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Admob Mcp?

Admob Mcp is a Model Context Protocol (MCP) server that exposes Google AdMob management, mediation waterfall operations, revenue analysis, and A/B experiments to MCP-compatible AI clients like Claude Code, Claude Desktop, Cursor, Windsurf, and Cline. It includes a local Rules Engine and Safety Layer that audits, verifies, and dry-runs mutating operations before touching the live AdMob account.

How to use Admob Mcp?

Enable the Google AdMob API in Cloud Console, download OAuth 2.0 Desktop credentials, create a Python 3.10+ virtual environment, install dependencies, configure .env with your PUBLISHER_ID and paths, run the one-time authorization flow (python admob_core/auth.py), then integrate with your AI client by specifying the command /path/to/.venv/bin/python -m admob_mcp and the required environment variables.

Key features of Admob Mcp

14 MCP tools for reporting, management, experiments, and diagnostics
Three resources: ad‑sources, app‑categories, format‑support
Two prompt templates: optimize_app and portfolio_health
Two‑stage safety pipeline: Rules Engine validation + audit logging
Local SQLite database for cached metrics (admob_metrics.db)
Asynchronous Google AdMob REST API v1beta wrapper

Use cases of Admob Mcp

Run a step‑by‑step monetization audit for a single app via optimize_app(app_id)
Perform a portfolio‑wide health check with portfolio_health
Create, update, or stop mediation A/B experiments
Analyze root causes of fill‑rate drops, match‑rate anomalies, and revenue alerts
Safely manage mediation groups with dry‑run and rule‑based blocking

常见问题

What are the runtime requirements for Admob Mcp?

Python 3.10 or newer, a Google Cloud project with the AdMob API enabled, OAuth 2.0 Desktop credentials, and an active AdMob publisher account.

How does authentication work?

OAuth 2.0 desktop flow: run `python admob_core/auth.py` to open a browser, authenticate with your Google AdMob account, and grant permissions. The resulting `token.json` is cached and auto‑refreshed on subsequent runs.

Where does data live?

Mediation metrics are synced into a local SQLite database (`admob_metrics.db`). Audit logs are written to `audit.log`. Credentials and tokens are stored in `credentials.json` and `token.json`.

What are the known limitations of the Rules Engine?

The Rules Engine blocks certain operations (e.g., adding a network that doesn’t support the ad format, using bidding networks on COPPA‑tagged apps) and warns about missing bidding partners or absent AdMob Network. All write tools support a `dry_run=True` parameter to preview changes without hitting the API.

How do I integrate Admob Mcp with Claude Desktop or Cursor?

For Claude Desktop, add a JSON entry to `claude_desktop_config.json` with the command, args, and environment variables. For Cursor, use the MCP settings UI to add a new command‑type server with the same command string.

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