SerpMCP

A Model Context Protocol (MCP) server for Google search using SERP API through the AceDataCloud API.

Perform Google searches and get structured results directly from Claude, VS Code, or any MCP-compatible client.

Features

• Web Search - Regular Google web search with structured results
• Image Search - Search for images with URLs and thumbnails
• News Search - Get latest news articles on any topic
• Video Search - Find videos from YouTube and other sources
• Places Search - Search for local businesses and places
• Maps Search - Find locations and geographic information
• Knowledge Graph - Get structured entity information
• Localization - Support for multiple countries and languages
• Time Filtering - Filter results by time range

Tool Reference

Quick Start

1. Get Your API Token

1. Sign up at AceDataCloud Platform
2. Go to the API documentation page
3. Click "Acquire" to get your API token
4. Copy the token for use below

2. Use the Hosted Server (Recommended)

AceDataCloud hosts a managed MCP server — no local installation required.

Endpoint: https://serp.mcp.acedata.cloud/mcp

All requests require a Bearer token. Use the API token from Step 1.

Claude.ai

Connect directly on Claude.ai with OAuth — no API token needed:

1. Go to Claude.ai Settings → Integrations → Add More
2. Enter the server URL: https://serp.mcp.acedata.cloud/mcp
3. Complete the OAuth login flow
4. Start using the tools in your conversation

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "serp": {
      "type": "streamable-http",
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cursor / Windsurf

Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):

{
  "mcpServers": {
    "serp": {
      "type": "streamable-http",
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

{
  "servers": {
    "serp": {
      "type": "streamable-http",
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Or install the Ace Data Cloud MCP extension for VS Code, which registers the hosted MCP servers with one-click setup.

JetBrains IDEs

1. Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
2. Click Add → HTTP
3. Paste:

{
  "mcpServers": {
    "serp": {
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

claude mcp add serp --transport http https://serp.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

Or add to your project's .mcp.json:

{
  "mcpServers": {
    "serp": {
      "type": "streamable-http",
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Cline

Add to Cline's MCP settings (.cline/mcp_settings.json):

{
  "mcpServers": {
    "serp": {
      "type": "streamable-http",
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Amazon Q Developer

Add to your MCP configuration:

{
  "mcpServers": {
    "serp": {
      "type": "streamable-http",
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Roo Code

Add to Roo Code MCP settings:

{
  "mcpServers": {
    "serp": {
      "type": "streamable-http",
      "url": "https://serp.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Continue.dev

Add to .continue/config.yaml:

mcpServers:
  - name: serp
    type: streamable-http
    url: https://serp.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

Zed

Add to Zed's settings (~/.config/zed/settings.json):

{
  "language_models": {
    "mcp_servers": {
      "serp": {
        "url": "https://serp.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

# Health check (no auth required)
curl https://serp.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://serp.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

# Install from PyPI
pip install mcp-serp
# or
uvx mcp-serp

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-serp

# Run (HTTP mode for remote access)
mcp-serp --transport http --port 8000

Claude Desktop (Local)

{
  "mcpServers": {
    "serp": {
      "command": "uvx",
      "args": ["mcp-serp"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

docker pull ghcr.io/acedatacloud/mcp-serp:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-serp:latest

Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.

Available Tools

Search Tools

Information Tools

Usage Examples

Basic Web Search

User: Search for information about artificial intelligence

Claude: I'll search for information about AI.
[Calls serp_google_search with query="artificial intelligence"]

News Search with Time Filter

User: What's the latest news about technology?

Claude: I'll search for recent tech news.
[Calls serp_google_news with query="technology", time_range="qdr:d"]

Localized Search

User: Find popular restaurants in Tokyo

Claude: I'll search for restaurants in Tokyo.
[Calls serp_google_places with query="popular restaurants Tokyo", country="jp"]

Image Search

User: Find images of the Northern Lights

Claude: I'll search for aurora borealis images.
[Calls serp_google_images with query="Northern Lights aurora borealis"]

Search Parameters

Search Types

Time Range Filters

Image Size Filters (for images search type)

large, medium, icon, 2mp, 4mp, 6mp, 8mp, 10mp, 12mp, 15mp, 20mp, 40mp, 70mp

Common Country Codes

Common Language Codes

Response Structure

Regular Search Results

• knowledge_graph: Entity information (company, person, etc.)
• answer_box: Direct answers
• organic: Regular search results with title, link, snippet
• people_also_ask: Related questions
• related_searches: Related queries

Image Search Results

• images: Image results with URLs and thumbnails

News Search Results

• news: News articles with source and date

Configuration

Environment Variables

Command Line Options

mcp-serp --help

Options:
  --version          Show version
  --transport        Transport mode: stdio (default) or http
  --port             Port for HTTP transport (default: 8000)

Development

Setup Development Environment

# Clone repository
git clone https://github.com/AceDataCloud/SerpMCP.git
cd SerpMCP

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # or `.venv\Scripts\activate` on Windows

# Install with dev dependencies
pip install -e ".[dev,test]"

Run Tests

# Run unit tests
pytest

# Run with coverage
pytest --cov=core --cov=tools

# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration

Code Quality

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools

Build & Publish

# Install build dependencies
pip install -e ".[release]"

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Project Structure

SerpMCP/
├── core/                   # Core modules
│   ├── __init__.py
│   ├── client.py          # HTTP client for SERP API
│   ├── config.py          # Configuration management
│   ├── exceptions.py      # Custom exceptions
│   └── server.py          # MCP server initialization
├── tools/                  # MCP tool definitions
│   ├── __init__.py
│   ├── search_tools.py    # Search tools
│   └── info_tools.py      # Information tools
├── prompts/                # MCP prompt templates
│   └── __init__.py
├── tests/                  # Test suite
│   ├── conftest.py
│   ├── test_client.py
│   └── test_config.py
├── deploy/                 # Deployment configs
│   └── production/
│       ├── deployment.yaml
│       ├── ingress.yaml
│       └── service.yaml
├── .env.example           # Environment template
├── .gitignore
├── CHANGELOG.md
├── Dockerfile             # Docker image for HTTP mode
├── docker-compose.yaml    # Docker Compose config
├── LICENSE
├── main.py                # Entry point
├── pyproject.toml         # Project configuration
└── README.md

API Reference

This server wraps the AceDataCloud Google SERP API:

• Google SERP API Documentation

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing)
5. Open a Pull Request

License

MIT License - see LICENSE for details.

Links

• AceDataCloud Platform
• Google SERP API
• Model Context Protocol
• MCP Python SDK

Made with love by AceDataCloud