Gemini Search

An MCP server that gives any AI agent rigorous, cited web search through Gemini CLI's Google Search grounding.

┌──────────────┐     STDIO      ┌──────────────────┐   child process   ┌─────────────┐
│  AI Agent    │◄──────────────►│  gemini-search   │──────────────────►│ Gemini CLI  │
│  (any MCP    │   JSON-RPC     │  MCP server      │  gemini-3-flash   │ Google Web  │
│   client)    │                └──────────────────┘   -preview         │ Search      │
└──────────────┘                                                       └─────────────┘

Why?

AI coding assistants (Claude, Kilo Code, Cursor, etc.) are powerful but blind to the live web. This MCP server fixes that by piping queries through Gemini CLI, which has built-in Google Search grounding — meaning every response is backed by real, current web results with citations.

Why use this over other paid search MCPs?

• 100% Free & Unlimited (relies on your local Google Cloud SDK / Gemini CLI auth)
• High Quality (uses Google's live search index and gemini-3-flash-preview model)
• No API keys to configure. If Gemini CLI works on your machine, this server works.

Tools

Tool	Description	Timeout
web_search	Quick factual lookups with source triangulation and confidence scoring	90s
deep_research	7-step research protocol with evidence grading [A/B/C/D] and opposing-view analysis	180s
fact_check	Forensic 5-phase verification pipeline with claim decomposition and precision audit	90s

Prerequisites

• Node.js ≥ 18
• Gemini CLI installed and authenticated (npm install -g @google/gemini-cli)
• Works on Windows, macOS, and Linux

Install

git clone https://github.com/leacvikas0/free-search-mcp-geminicli.git
cd free-search-mcp-geminicli
npm install

Setup

Add to your MCP client config:

Claude Desktop / Antigravity / Generic MCP Client

{
  "mcpServers": {
    "gemini-search": {
      "command": "node",
      "args": ["/absolute/path/to/free-search-mcp-geminicli/server.js"],
      "env": {}
    }
  }
}

Kilo Code (VS Code)

Settings → MCP Configuration → Edit Global MCP File:

{
  "mcpServers": {
    "gemini-search": {
      "command": "node",
      "args": ["/absolute/path/to/free-search-mcp-geminicli/server.js"],
      "env": {},
      "trust": true
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "gemini-search": {
      "command": "node",
      "args": ["/absolute/path/to/free-search-mcp-geminicli/server.js"]
    }
  }
}

How It Works

1. Your AI agent calls an MCP tool (e.g., web_search)
2. The server writes the query to a temp file and pipes it into gemini -m gemini-3-flash-preview --output-format json
3. Gemini CLI uses its built-in google_web_search grounding to search the live web
4. The server parses the JSON response and returns clean, cited results
5. Your AI agent gets grounded, accurate web research

Each tool has a carefully crafted system prompt that enforces:

• Source triangulation — verify claims from 2+ independent sources
• Anti-hallucination rules — never fabricate URLs, stats, or quotes
• Evidence grading — [A] through [D] ratings on claim confidence
• Conflict detection — surface disagreements between sources instead of hiding them

Configuration

The model is set to gemini-3-flash-preview by default. To change it, edit the MODEL constant at the top of server.js:

const MODEL = "gemini-3-flash-preview"; // Change to any Gemini model

License

MIT