gemini-search-mcp
MCP server for web search powered by Google AI Mode (Gemini). Free, unlimited, no API key.
README
gemini-search-mcp
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<p align="center"> MCP server for web search powered by Google AI Mode (Gemini). Free, unlimited, no API key. </p>
What is this
An MCP server that gives any AI agent (Claude, Cursor, Windsurf, etc.) the ability to search the web in real-time using Google's AI Mode — the same Gemini-powered search that lives in the "AI Mode" tab on Google Search.
Think of it as a free, unlimited alternative to Grok MCP / Tavily / SerpAPI, backed by Google's search index.
Features
- Free: No API key, no subscription, no quota
- Unlimited: 60+ requests/min with zero rate limiting
- Google quality: Powered by Gemini + Google Search (grounded in real web results)
- MCP native: Works with Claude Desktop, Claude Code, Cursor, Windsurf, Cline
- Also ships OpenAI API:
/v1/chat/completionsfor non-MCP clients - Fast: ~1.5s average response time
Quick Start
pip install -e .
# Optional: install the undetected-chromedriver backend for CAPTCHA probes.
pip install -e '.[undetected]'
MCP Server (for AI agents)
gemini-search-mcp
OpenAI-compatible API
gemini-search --port 8080
MCP Integration
Claude Code
claude mcp add gemini-search -- gemini-search-mcp
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"gemini-search": {
"command": "gemini-search-mcp",
"args": [],
"env": {
"CDP_URL": "http://127.0.0.1:9222"
}
}
}
}
Cursor / Windsurf
Same pattern — point to gemini-search-mcp as an stdio MCP server.
MCP Tools
| Tool | Description |
|---|---|
web_search(query) |
Search the web and get a synthesized answer grounded in real-time results |
ask(prompt) |
General question — AI Mode auto-decides whether to search the web |
Examples
web_search("latest AI regulation news 2026")
→ "The EU AI Act enforcement began on June 1, 2026, requiring..."
web_search("Bitcoin price today")
→ "As of June 30, 2026, Bitcoin is trading at $59,687 USD..."
ask("what is 1847 * 293")
→ "541171"
OpenAI API Usage
curl http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{"model":"gemini-search","messages":[{"role":"user","content":"What happened in the news today?"}]}'
| Field | Value |
|---|---|
| Base URL | http://localhost:8080/v1 |
| API Key | anything |
| Model | gemini-search |
Environment Variables
| Variable | Default | Description |
|---|---|---|
CDP_URL |
(none) | Chrome DevTools URL. If set, connects to existing Chrome instead of launching one |
BROWSER_CHANNEL |
chrome |
Browser to use: chrome, msedge, chromium |
HEADLESS |
1 |
Set to 0 to show browser window |
GEMINI_SEARCH_USER_DATA_DIR |
(none) | Persistent Chrome profile directory. Reuses cookies across runs and is not deleted on shutdown |
GEMINI_SEARCH_CDP_PORT |
19250 |
CDP port used for self-launched Chrome |
GEMINI_SEARCH_BROWSER_BACKEND |
subprocess |
Browser launcher: subprocess or undetected |
GEMINI_SEARCH_PROXY_SERVER |
(none) | Chrome proxy server, e.g. socks5://127.0.0.1:7897 |
GEMINI_SEARCH_CHROMEDRIVER |
(none) | Chromedriver executable used by the undetected backend |
Persistent Chrome profile / CAPTCHA priming
If Google shows /sorry/ CAPTCHA for a fresh temporary profile, prime a persistent profile once in a visible Chrome window, then reuse the same directory in headless mode:
# 1) Visible first run: solve CAPTCHA manually if Google asks.
gemini-search --no-headless --user-data-dir "$HOME/.local/share/gemini-search-mcp/chrome-profile"
# 2) Later runs: reuse the same cookies headlessly.
GEMINI_SEARCH_USER_DATA_DIR="$HOME/.local/share/gemini-search-mcp/chrome-profile" gemini-search
For Windows-side validation from WSL, run the probe with Windows Python through PowerShell so it launches Windows Chrome:
$profile = Join-Path $env:TEMP 'gemini-search-mcp-persistent-profile'
python .\scripts\windows_chrome_profile_probe.py `
--profile-dir $profile `
--mode two-phase `
--out .\headless-reuse-result.json
Success evidence is ok=true and stages.headless_reuse.captcha=false in the JSON output.
undetected-chromedriver CAPTCHA probe
When a normal Chrome subprocess gets a Google /sorry/ CAPTCHA, install the optional backend and run the reusable probe against google.com.hk:
pip install -e '.[undetected]'
python scripts/uc_google_probe.py \
--proxy socks5://127.0.0.1:7897 \
--out-json uc-probe.json
Use the backend only when the probe reports ok=true, captcha=false, and successful_for_engine_integration=true.
gemini-search \
--browser-backend undetected \
--proxy-server socks5://127.0.0.1:7897 \
--chromedriver-path /path/to/chromedriver \
--no-headless
Observed on Windows Chrome for Testing 148 through Clash: headed UC passed (captcha=false and AI Mode tokens present), while headless UC hit Google /sorry/.
How It Works
Google rate-limits by TLS fingerprint quality — not by IP. Automated HTTP clients (curl, requests, httpx) get throttled after a few requests. But a real Chrome browser's fetch() calls are trusted unconditionally.
This tool runs a single real Chrome tab and executes all queries as fetch() inside it over CDP, giving every request an authentic Chrome TLS/HTTP2 fingerprint. Google sees normal browser traffic and applies no rate limits. The optional undetected backend still uses the same CDP query path after launch.
Agent calls web_search("query")
→ Chrome Runtime.evaluate(fetch)
→ Google Search AI Mode (token extraction + folwr endpoint)
→ Parse answer from HTML response
→ Return to agent
Comparison
| gemini-search-mcp | Grok MCP | Tavily | |
|---|---|---|---|
| Cost | Free | xAI API key ($) | API key ($) |
| Rate limit | None | API quota | API quota |
| Search backend | Google Search | Grok + web | Proprietary |
| Answer quality | Gemini synthesized | Grok synthesized | Extracted snippets |
| Setup | Chrome + CDP | API key | API key |
Docker
docker compose up -d
Requirements
- Python 3.10+
- Chrome, Edge, or Chromium
- Runtime dependencies from
pyproject.toml - Optional:
undetected-chromedriverandseleniumviapip install -e '.[undetected]'
Limitations
- Requires Chrome/Edge/Chromium installed
- No conversation memory between requests
- Answer extraction relies on Google's DOM structure (may break on updates)
- Streaming is chunked, not per-token
Acknowledgments
- GenericAgent — 本项目核心开发依仗 GA 提供的 AI 能力
- linux.do community
License
MIT
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