Which integrations are available for this server?

Uses Google Search grounding to retrieve live web results, current documentation, news, and verified source citations. Connects to Google Gemini models via the Gemini API to generate answers grounded in real-time web search results.

How do I use gemini-search-mcp?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@gemini-search-mcp what's the latest stable version of Node.js and link to docs?" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

gemini-search-mcp

by kazimshah39

Overview Schema Source Related Servers Discussions Admin

JavaScript

Remote

gemini-search-mcp

A lightweight, zero-dependency Model Context Protocol (MCP) server that provides real-time web search with Google Search grounding powered by Google Gemini models.

Give your AI coding assistants (Claude Desktop, Cursor, Antigravity, OpenCode, Zed, Cline) real-time access to the live web, current documentation, APIs, and news with verified source citations.

Features

⚡ Zero External Dependencies: Pure Node.js ESM. Instant npx downloads and cold starts without bundle bloat.
🔍 Google Search Grounding: Leverages Google's native grounding tools for high accuracy, freshness, and relevance.
📚 Clean Markdown Citations: Automatically extracts answers and appends deduplicated markdown source links.
🧠 Thought-Filtering: Automatically filters internal model reasoning tokens to keep tool outputs compact and relevant.
⚙️ Custom Proxy & Model Support: Compatible with official Google Gemini API as well as custom endpoints (e.g. CLIProxyAPI, Open-WebUI, or local gateways).

Related MCP server: Crawl4AI RAG MCP Server

Quickstart

You don't need to install anything globally. Run directly via npx:

npx -y @kazimshah39/gemini-search-mcp

Get an API Key

Get a Google Gemini API key from Google AI Studio.

Configuration

Add the server to your MCP client configuration file:

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "gemini-search": {
      "command": "npx",
      "args": ["-y", "@kazimshah39/gemini-search-mcp"],
      "env": {
        "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
      }
    }
  }
}

Cursor

In .cursor/mcp.json or Cursor Settings -> Features -> MCP:

{
  "mcpServers": {
    "gemini-search": {
      "command": "npx",
      "args": ["-y", "@kazimshah39/gemini-search-mcp"],
      "env": {
        "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
      }
    }
  }
}

Antigravity / OpenCode

In your workspace .mcp.json:

{
  "mcpServers": {
    "gemini-search": {
      "command": "npx",
      "args": ["-y", "@kazimshah39/gemini-search-mcp"],
      "env": {
        "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
      }
    }
  }
}

Environment Variables

Variable	Required	Default	Description
`GEMINI_API_KEY`	Yes	`undefined`	Your Google Gemini API key or proxy authorization key.
`GEMINI_MODEL`	No	`gemini-2.5-flash`	The Gemini model to use for grounded searches (e.g., `gemini-2.5-flash`, `gemini-2.0-flash`, `gemini-3.8-flash`).
`GEMINI_BASE_URL`	No	`https://generativelanguage.googleapis.com/v1beta`	Custom base endpoint if using a custom gateway or reverse proxy.
`GEMINI_PROXY_URL`	No	`undefined`	Alias for `GEMINI_BASE_URL` (e.g. `http://127.0.0.1:8317/v1beta`).
`GEMINI_TIMEOUT_MS`	No	`35000`	Request timeout in milliseconds (default 35 seconds).

Example with Local Proxy / Custom Gateway

If you route requests through a local proxy (such as CLIProxyAPI):

{
  "mcpServers": {
    "gemini-search": {
      "command": "npx",
      "args": ["-y", "@kazimshah39/gemini-search-mcp"],
      "env": {
        "GEMINI_API_KEY": "YOUR_PROXY_KEY",
        "GEMINI_PROXY_URL": "http://127.0.0.1:8317/v1beta",
        "GEMINI_MODEL": "gemini-3.8-flash"
      }
    }
  }
}

Tool Reference

`gemini_search`

Search the live web using Google Search grounding via Gemini. Returns current real-time facts, documentation, news, and verified sources.

Input Schema:

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The search query or question to research on Google."
    }
  },
  "required": ["query"]
}

Local Development & Testing

Clone the repository and test locally:

git clone https://github.com/kazimshah39/gemini-search-mcp.git
cd gemini-search-mcp

# Test running directly
export GEMINI_API_KEY="your-key-here"
node ./bin/cli.js

You can test JSON-RPC communication by piping JSON:

echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{}}' | node ./bin/cli.js

License

MIT © Kazim Shah

Available Tools

1 tool

gemini_searchA

Search the live web using Google Search grounding via Gemini. Returns current real-time facts, documentation, news, and verified sources.

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes	The search query or question to research on Google.

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the retrieval mechanism (Google Search grounding) and the rough shape of results, but says nothing about latency, rate limits, citation behavior, or freshness guarantees for a live-web dependency.

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?

Two tight sentences with the action front-loaded and the return content immediately after. No filler, no repetition of the tool name.

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?

For a simple one-parameter read tool with no output schema, the description compensates by describing what comes back (real-time facts, docs, news, verified sources). A note on recency or citation handling would make it fully complete.

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

Parameters3/5

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

Schema coverage is 100% for the single 'query' parameter, so the schema already documents it fully. The description adds no syntax guidance (natural-language question vs keyword query) beyond what the schema states, making the baseline 3 appropriate.

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?

States a specific verb (Search), resource (the live web via Google Search grounding through Gemini), and even the nature of the payoff (current real-time facts, documentation, news, verified sources). No siblings exist to differentiate from, but the purpose is unambiguous without opening the schema.

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?

Usage is only implied: the emphasis on 'live', 'current real-time facts' signals when this tool beats a static knowledge source, but it never explicitly says when to use it, when not to, or what alternative it replaces. Adequate but leaves routing to inference.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

1 tool updatev1.0.0Oct 20, 2026
- First observedgemini_search

Deploy Server

Give agents eyes on the webHosted screenshot MCP. Send a URL, get a pixel-perfect image. $0.002 per grab. Works with Claude, Cursor, and Codex.grabbit.liveAd

TDQS

A4/5.0

Scored 2026-10-20 15:25 across 1 tool

Disambiguation5/5

Only one tool exists, so there is no risk of misselection or overlapping purpose; an agent cannot confuse it with another tool.

Naming Consistency5/5

The sole tool uses clear snake_case with a descriptive noun/verb structure (gemini_search); no inconsistency is possible with a single tool.

Tool Count4/5

A single search tool is reasonable for a narrowly scoped web-search server, though it is below the typical 3–15 range and could feel thin if broader search operations are expected.

Completeness4/5

The tool covers the core web-search operation and returns current facts, docs, news, and sources, but it lacks advanced parameters (e.g., result count, filters, pagination) that a full search surface might offer.

Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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gemini-search-mcp

Features

Quickstart

Get an API Key

Configuration

Claude Desktop

Cursor

Antigravity / OpenCode

Environment Variables

Example with Local Proxy / Custom Gateway

Tool Reference

gemini_search

Local Development & Testing

License

Available Tools

TDQS

Tool Schema Changelog

TDQS

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

OpenAI Web Search MCP Server

Crawl4AI RAG MCP Server

ContextEngine MCP Server

serpdiveofficial

`gemini_search`