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by surendranb · MCP Server · ★ 242
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🔒 Is google-analytics-mcp safe to install? View the security audit →
Google Analytics MCP Server mcp-name: io.github.surendranb/google-analytics-mcp Connect Google Analytics 4 data to AI agents, agentic workflows, and MCP clients. Give agents analysis-ready access to website traffic, user behavior, and performance data with schema discovery, server-side aggregation, and safe defaults that reduce data wrangling. Built for: AI agents, analyst copilots, and MCP runtimes across Claude, ChatGPT, Cursor, Windsurf, and custom hosts. I also b
| Stars | 242 |
| Forks | 48 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 74.1495540826194/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-21 |
| Created | 2025-05-24 |
| Platforms | browser, claude-code, cli, gemini, mcp, python |
| Est. Tokens | ~17k |
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google-analytics-mcp is Google Analytics 4 data to AI agents, agentic workflows, and MCP clients. Give agents analysis-ready access to website traffic, user behavior, and performance data with schema discovery, server-side a. It is categorized as a MCP Server with 242 GitHub stars.
google-analytics-mcp is primarily written in Python. It covers topics such as ai-agent, ai-agents, analytics.
You can find installation instructions and usage details in the google-analytics-mcp GitHub repository at github.com/surendranb/google-analytics-mcp. The project has 242 stars and 48 forks, indicating an active community.
google-analytics-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to google-analytics-mcp on Agent Skills Hub include atlassian-mcp-server, arcade-mcp, maverick-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: