MCP.Market

Google AI Search MCP server

by shariqriazz·io.github.shariqriazz/google-ai-search-mcp·v1.1.1·7 stars
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Google AI search and documentation tools for MCP clients using Vertex AI or the Gemini API.

B78/100grade B
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Safety scan
B78/100

full report

Adoption
Growing

7 stars179 downloads/wk

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Google AI Search MCP tools (7)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • answer_query_websearch

    Answers a natural language query using the configured Vertex AI model (…) enhanced with Google Search results for up-to-date information. Requires a 'query' string.

  • architecture_pattern_recommendation

    Suggests architecture patterns for specific use cases based on industry best practices. Provides implementation examples and considerations for the recommended patterns. Includes diagrams and explanations of pattern benefits and tradeoffs. Uses the configured Vertex AI model (…) with Google Search. Requires 'requirements' and 'tech_stack'.

  • code_analysis_with_docs

    Analyzes code snippets by comparing them with best practices from official documentation found via web search. Identifies potential bugs, performance issues, and security vulnerabilities. Uses the configured Vertex AI model (…) with Google Search. Requires 'code', 'language', and 'analysis_focus'.

  • explain_topic_with_docs

    Provides a detailed explanation for a query about a specific software topic by synthesizing information primarily from official documentation found via web search. Focuses on comprehensive answers, context, and adherence to documented details. Uses the configured Vertex AI model (…) with Google Search. Requires 'topic' and 'query'.

  • generate_project_guidelines

    Generates a structured project guidelines document (e.g., Markdown) based on a specified list of technologies and versions (tech stack). Uses web search to find the latest official documentation, style guides, and best practices for each component and synthesizes them into actionable rules and recommendations. Uses the configured Vertex AI model (…) with Google Search. Requires 'tech_stack'.

  • get_doc_snippets

    Provides precise, authoritative code snippets or concise answers for technical queries by searching official documentation. Focuses on delivering exact solutions without unnecessary explanation. Uses the configured Vertex AI model (…) with Google Search. Requires 'topic' and 'query'.

  • technical_comparison

    Compares multiple technologies, frameworks, or libraries based on specific criteria. Provides detailed comparison tables with pros/cons and use cases. Includes version-specific information and compatibility considerations. Uses the configured Vertex AI model (…) with Google Search. Requires 'technologies' and 'criteria'.

Public scan report

scanner v0.1.10 · 2026-11-04 · same rubric, same numbers if you re-run it

no findings
  • Code scan15 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 58 days ago12/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 78/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Google AI Search MCP compares

Against every graded Web search MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
78/100
higher than 62% of 3,470 Web search servers
Tools
7
the typical Web search server has 5
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
7
more than 83% of 1,786 Web search servers
Downloads a week
179
more than 69% of 827 Web search servers with a package

What its tools let an agent do: 6 read · 1 create

Install Google AI Search MCP in Claude Code, Cursor or VS Code

Runs npx -y google-ai-search-mcp on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add google-ai-search-mcp -- npx -y google-ai-search-mcp
Add to Cursor

What the publisher says

From the Google AI Search MCP repository's README, as published. We do not edit it. Read it on GitHub

Google AI Search MCP

This project implements a Model Context Protocol (MCP) server that provides a comprehensive suite of Google AI-powered search and documentation tools specifically designed to help AI coders overcome LLM knowledge gaps and information limitations.

Implementation notes

Provider selection and credentials are resolved at runtime, so a tool being listed does not prove that its upstream provider is configured or reachable. Treat model-produced comparisons, architecture guidance, and security analysis as material to verify against the cited primary sources rather than deterministic findings.

For a source-linked comparison of the design pressures across this project and six other public MCP implementations, see What building seven MCP servers taught me about production MCP.

Features

  • Provides access to Google AI models (Vertex AI and Gemini API) via specialized MCP tools.
  • Focuses on real-time information retrieval and documentation-based analysis.
  • Supports web search grounding for current information that LLMs lack.
  • Configurable model ID, temperature, streaming behavior, max output tokens, and retry settings via environment variables.
  • Uses streaming API by default for potentially better responsiveness.
  • Includes basic retry logic for transient API errors.
  • Minimal safety filters applied (BLOCK_NONE) to reduce potential blocking (use with caution).

Tools Provided

Core Search & Documentation Tools

  • answerquerywebsearch: Developer-focused natural language queries with automatic technical detection, enhanced search methodology, and comprehensive code formatting using Google AI with real-time search results.
  • explaintopicwith_docs: Streamlined technical explanations with improved debugging scenarios, synthesizing information from official documentation with reduced verbosity and enhanced troubleshooting guidance.
  • getdocsnippets: Enhanced code snippet retrieval with progressive complexity examples, advanced search patterns, version-specific targeting, and comprehensive context for technical queries from official documentation.
  • generateprojectguidelines: Generates comprehensive structured project guidelines documents based on specified technologies, using web search for current best practices and industry standards.

Advanced Analysis Tools

  • codeanalysiswith_docs: Evidence-based code analysis with standardized citations, severity categorization, and actionable recommendations by comparing code against official documentation best practices.
  • technical_comparison: Produces technology comparisons across requested criteria using current search context where available. Verify quantitative or market claims against the cited primary sources.
  • architecturepatternrecommendation: Produces architecture options, tradeoffs, and implementation considerations for a described use case. Validate the recommendation against the system's actual constraints before adopting it.

(Note: Input/output schemas for each tool are defined in their respective files within src/tools/ and exposed via the MCP server.)

Prerequisites

  • Node.js (v18+)
  • Bun (npm install -g bun)
  • Google Cloud Project with Billing enabled (if using Vertex AI).
  • Vertex AI API enabled in the GCP project (if using Vertex AI).
  • Google Cloud Authentication configured in your environment (Application Default Credentials via gcloud auth application-default login is recommended, or a Service Account Key) OR Gemini API key.

Setup & Installation

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Google AI Search MCP: common questions

Is Google AI Search MCP server safe?
Mostly: it is graded B (78/100). Read the Google AI Search MCP safety report
How do I install Google AI Search MCP?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Google AI Search MCP need an API key?
Yes. The registry entry asks for GEMINI_API_KEY.
Is Google AI Search MCP maintained?
The last commit was 58 days ago (2026-09-07). The latest release is v1.1.1.
What can I use instead of Google AI Search MCP?
Servers from other publishers that do the same job: GitHits MCP server, Google Maps MCP Server and Sui Knowledge Base (kapa.ai) MCP server.
How does Google AI Search MCP compare with other Web search MCP servers?
safety score 78/100 (higher than 62% of 3,470 Web search servers); tools 7 (the typical Web search server has 5); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Google AI Search MCP

Same job from other publishers: the closest match first, then the best rated.

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