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MCP server CX Codex

Google AI Search MCP — Claude Code MCP server: search and setup

This MCP server gives AI coding clients Google AI web search and documentation tools. Use it when answers need current technical sources.

Install into Claude Code · Platform CLI All methods and platforms ↓

claude mcp add --env AI_PROVIDER=<AI_PROVIDER> --env GOOGLE_CLOUD_PROJECT=<GOOGLE_CLOUD_PROJECT> --env GOOGLE_CLOUD_LOCATION=<GOOGLE_CLOUD_LOCATION> --env GEMINI_API_KEY=<GEMINI_API_KEY> --transport stdio google-ai-search-mcp -- npx -y google-ai-search-mcp

What Google AI Search MCP does

Google AI Search MCP connects MCP clients to tools backed by Vertex AI or the Gemini API. It can retrieve current web information, explain technical subjects from official documentation, find code snippets, and draft project guidance.

The server also offers code review against documented practices, technology comparisons, and architecture options for a described use case. Environment variables control the provider, model, temperature, streaming, output-token limit, and retry behavior. Treat generated comparisons and architecture advice as material to verify against primary sources.

You need Node.js v18+, Bun, and credentials for a provider. Vertex AI requires a billed Google Cloud Project, the Vertex AI API, and Google Cloud authentication; Gemini requires GEMINI_API_KEY. Without a configured provider, the server cannot call the model.

What it helps with

retrieve current answers about a library
explain a topic from official documentation
find a version-specific code snippet
compare technologies using chosen criteria
review code against documented practices

Example prompts for the agent

Use answer_query_websearch to find the current authentication setup for this library.
Use explain_topic_with_docs to explain this error from official documentation.
Use technical_comparison to compare technology-a and technology-b by cost and constraints.

How to install Google AI Search MCP

Platform CLI

claude mcp add --env AI_PROVIDER=<AI_PROVIDER> --env GOOGLE_CLOUD_PROJECT=<GOOGLE_CLOUD_PROJECT> --env GOOGLE_CLOUD_LOCATION=<GOOGLE_CLOUD_LOCATION> --env GEMINI_API_KEY=<GEMINI_API_KEY> --transport stdio google-ai-search-mcp -- npx -y google-ai-search-mcp

Replace <…> with your own values

Platform CLI

codex mcp add google-ai-search-mcp --env AI_PROVIDER=<AI_PROVIDER> --env GOOGLE_CLOUD_PROJECT=<GOOGLE_CLOUD_PROJECT> --env GOOGLE_CLOUD_LOCATION=<GOOGLE_CLOUD_LOCATION> --env GEMINI_API_KEY=<GEMINI_API_KEY> -- npx -y google-ai-search-mcp

Replace <…> with your own values

Config file

{
    "mcpServers": {
        "google-ai-search-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "google-ai-search-mcp"
            ],
            "env": {
                "AI_PROVIDER": "<AI_PROVIDER>",
                "GOOGLE_CLOUD_PROJECT": "<GOOGLE_CLOUD_PROJECT>",
                "GOOGLE_CLOUD_LOCATION": "<GOOGLE_CLOUD_LOCATION>",
                "GEMINI_API_KEY": "<GEMINI_API_KEY>"
            }
        }
    }
}

Replace <…> with your own values

Config file

{
    "servers": {
        "google-ai-search-mcp": {
            "type": "stdio",
            "command": "npx",
            "args": [
                "-y",
                "google-ai-search-mcp"
            ],
            "env": {
                "AI_PROVIDER": "<AI_PROVIDER>",
                "GOOGLE_CLOUD_PROJECT": "<GOOGLE_CLOUD_PROJECT>",
                "GOOGLE_CLOUD_LOCATION": "<GOOGLE_CLOUD_LOCATION>",
                "GEMINI_API_KEY": "<GEMINI_API_KEY>"
            }
        }
    }
}

Replace <…> with your own values

Platform CLI

gemini mcp add -e AI_PROVIDER=<AI_PROVIDER> -e GOOGLE_CLOUD_PROJECT=<GOOGLE_CLOUD_PROJECT> -e GOOGLE_CLOUD_LOCATION=<GOOGLE_CLOUD_LOCATION> -e GEMINI_API_KEY=<GEMINI_API_KEY> google-ai-search-mcp npx -y google-ai-search-mcp

Replace <…> with your own values

Step by step, with commands for each platform: How to add an MCP server to Claude Code, Codex, Cursor, VS Code, Gemini CLI and more

Questions about Google AI Search MCP

How do I install Google AI Search MCP in Claude Code?

Run claude mcp add google-ai-search-mcp -e GEMINI_API_KEY=<GEMINI_API_KEY> -- npx -y google-ai-search-mcp.

What does Google AI Search MCP do?

It exposes Google AI tools for web search, official documentation lookup, code analysis, technology comparisons, and architecture guidance to MCP clients.

What credentials does the server need?

Set AI_PROVIDER to vertex or gemini. Vertex AI needs GOOGLE_CLOUD_PROJECT and Google Cloud authentication; Gemini needs GEMINI_API_KEY.

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