Ads MCP: MCP server, setup and security

What Ads MCP does

According to its repository: “Manage Google, Meta, Amazon, TikTok, LinkedIn & ChatGPT ads. 430 tools for campaigns & analytics.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Ads MCP is listed under Data science and visualization, a category of 48 servers in the directory, where it ranks #19 by stars.

Topics declared by the repository: advertising, ai-agent, chatgpt, claude, google-ads, linkedin-ads.

Installing and connecting Ads MCP

Distribution modes declared in the official MCP registry:

• remote server (streamable-http): you connect to it by URL, with nothing to install locally

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: Jupyter Notebook.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Ads MCP. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on October 27, 2025, the amekala/ads-mcp repository has 105 stars and 23 forks, with 9 open issues. It has more stars than 68% of the servers in the directory. It received changes this month. Version published in the registry: 1.2.0 (July 14, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.