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by PleasePrompto · MCP Server · ★ 151
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🔒 Is google-ai-mode-mcp safe to install? View the security audit →
Google AI Mode MCP Server Supercharge Any LLM's Web Research with Google AI Mode For: All MCP-compatible LLMs (Claude, Cursor, Cline, Windsurf, Zed, etc.) Transform your LLM's online research capabilities by connecting it directly to Google's AI Mode—getting AI-synthesized answers from 100+ sources instead of scattered search results. Why This Matters Most built-in web research is mediocre. This MCP server gives any LLM professional-grade research by tapping into Google's AI Mode—the same technology that synthesizes information from dozens of websites into one cited answer. Example Use Cases: "Next.js 15 App Router best practices 2026 with server components examples" → AI-synthesized coding guide with inline citations [1][2][3] "Compare PostgreSQL vs MySQL JSON performance 2026, include benchmarks" → Technical comparison table w
| Stars | 151 |
| Forks | 19 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 82.18682080468/100 |
| Last Updated | 2026-09-10 |
| Created | 2026-01-03 |
| Platforms | browser, claude-code, cli, codex, mcp, node |
| Est. Tokens | ~8k |
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google-ai-mode-mcp is MCP server for free Google AI Mode search with citations. Query optimization, CAPTCHA handling, multi-agent support. Works with Claude Code, Cursor, Cline, Windsurf.. It is categorized as a MCP Server with 151 GitHub stars.
google-ai-mode-mcp is primarily written in TypeScript. It covers topics such as browser-automation, citations, claude-code.
You can find installation instructions and usage details in the google-ai-mode-mcp GitHub repository at github.com/PleasePrompto/google-ai-mode-mcp. The project has 151 stars and 19 forks, indicating an active community.
google-ai-mode-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to google-ai-mode-mcp on Agent Skills Hub include deterministic-agent-control-protocol, VSCode-Perplexity-MCP, Overture. 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: