Skip to main content
Glama
mkih76

gemini-search-mcp

by mkih76

web_search

Read-only

Search the web using Google AI Mode to get a synthesized answer with sources from current web pages, news, and data.

Instructions

Search the web using Google AI Mode and get a synthesized answer with sources.

Uses Google Search's AI Mode (powered by Gemini) to search the web in real-time and return a comprehensive, grounded answer. Results include information from current web pages, news, and data.

This is equivalent to using Google Search's "AI Mode" tab — the AI reads multiple web sources and synthesizes an answer, similar to Perplexity or Grok's web search, but powered by Google's search index.

Args: query: Search query or question. Can be anything you'd type into Google. Examples: "latest news about AI regulation", "Bitcoin price today", "how does mRNA vaccine work", "Python asyncio best practices 2026"

Returns: A synthesized answer based on real-time web search results. The answer is grounded in actual web content found by Google.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations (readOnlyHint=true) indicate read-only operation, which matches the description. Description adds detail about real-time search, synthesis, and grounding in web content, going beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise and well-structured: front-loaded with purpose, then details, equivalence explanation, and structured Args/Returns sections. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and presence of an output schema, the description covers purpose, usage, and behavior well. Minor gap: no mention of potential limitations or failure modes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must compensate. It provides comprehensive semantics for the 'query' parameter: describes it as a search query or question, gives examples, and clarifies it can be anything typed into Google.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb ('search'), resource ('web'), and mode ('Google AI Mode') with a synthesized answer. It distinguishes from the sibling tool 'ask' by specifying it uses Google's AI Mode, which is a specific search mode.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides examples of queries and states it is equivalent to Google's AI Mode tab, but does not explicitly say when not to use it or compare to alternatives like 'ask'. No exclusion criteria or alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mkih76/gemini-search-mcp-cn'

If you have feedback or need assistance with the MCP directory API, please join our Discord server