by cohnen · MCP Server · ★ 445
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
An MCP tool that connects Google Ads with Claude AI/Cursor and others, allowing you to analyze your advertising data through natural language conversations. This integration gives you access to campaign information, performance metrics, keyword analytics, and ad management—all through simple chat with Claude, Cursor or Windsurf.
| Stars | 445 |
| Forks | 98 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 48.75/100 |
| Open Issues | 11 |
| Last Updated | 2025-10-16 |
| Created | 2025-03-20 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~11k |
These tools work well together with mcp-google-ads for enhanced workflows:
Looking for a mcp-google-ads alternative? If you're comparing mcp-google-ads with other mcp server tools, these 2 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
The Google Ads MCP Server is an implementation of the Model Context Protocol (MCP) that enables Large Language
An MCP server that gives your AI assistant read + write access to Google Ads and GA4 — with safety guardrails
Explore other popular mcp server tools:
mcp-google-ads is An MCP tool that connects Google Ads with Claude AI/Cursor and others, allowing you to analyze your advertising data through natural language conversations. This integration gives you access to campai. It is categorized as a MCP Server with 445 GitHub stars.
mcp-google-ads is primarily written in Python. It covers topics such as ai, claude, google-ads.
You can find installation instructions and usage details in the mcp-google-ads GitHub repository at github.com/cohnen/mcp-google-ads. The project has 445 stars and 98 forks, indicating an active community.
mcp-google-ads is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-google-ads on Agent Skills Hub include google_ads_mcp, adloop. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.