Skip to main content

Google Scholar MCP Server

smithery badge

🔍 Enable AI assistants to search and access Google Scholar papers through a simple MCP interface.

The Google Scholar MCP Server provides a bridge between AI assistants and Google Scholar through the Model Context Protocol (MCP). It allows AI models to search for academic papers and access their content in a programmatic way.

✨ Core Features

  • 🔎 Paper Search: Query Google Scholar papers with custom search strings or advanced search parameters ✅
  • 🚀 Efficient Retrieval: Fast access to paper metadata ✅
  • 👤 Author Information: Retrieve detailed information about authors ✅
  • 📊 Research Support: Facilitate academic research and analysis ✅

🚀 Quick Start

Installing Manually

Installing via Smithery

To install google-scholar Server for Claude Desktop automatically via Smithery:

claude

npx -y @smithery/cli@latest install @JackKuo666/google-scholar-mcp-server --client claude --config "{}"

Cursor

Paste the following into Settings → Cursor Settings → MCP → Add new server:

  • Mac/Linux
npx -y @smithery/cli@latest run @JackKuo666/google-scholar-mcp-server --client cursor --config "{}" 

Windsurf

npx -y @smithery/cli@latest install @JackKuo666/google-scholar-mcp-server --client windsurf --config "{}"

CLine

npx -y @smithery/cli@latest install @JackKuo666/google-scholar-mcp-server --client cline --config "{}"
  1. Clone the repository:

    git clone https://github.com/JackKuo666/google-scholar-MCP-Server.git
    cd google-scholar-MCP-Server
    
  2. Install the required dependencies:

    pip install -r requirements.txt
    

For development:

# Clone and set up development environment
git clone https://github.com/JackKuo666/Google-Scholar-MCP-Server.git
cd Google-Scholar-MCP-Server

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt

📊 Usage

Start the MCP server:

python google_scholar_server.py

Once the server is running, you can use the provided MCP tools in your AI assistant or application. Here are some examples of how to use the tools:

Example 1: Search for papers using keywords

result = await mcp.use_tool("search_google_scholar_key_words", {
    "query": "artificial intelligence ethics",
    "num_results": 5
})
print(result)

Example 2: Perform an advanced search

result = await mcp.use_tool("search_google_scholar_advanced", {
    "query": "machine learning",
    "author": "Hinton",
    "year_range": [2020, 2023],
    "num_results": 3
})
print(result)

Example 3: Get author information

result = await mcp.use_tool("get_author_info", {
    "author_name": "Geoffrey Hinton"
})
print(result)

These examples demonstrate how to use the three main tools provided by the Google Scholar MCP Server. Adjust the parameters as needed for your specific use case.

Usage with Claude Desktop

Add this configuration to your claude_desktop_config.json:

(Mac OS)

{
  "mcpServers": {
    "google-scholar": {
      "command": "python",
      "args": ["-m", "google_scholar_mcp_server"]
      }
  }
}

(Windows version):

{
  "mcpServers": {
    "google-scholar": {
      "command": "C:\\Users\\YOUR\\PATH\\miniconda3\\envs\\mcp_server\\python.exe",
      "args": [
        "D:\\code\\YOUR\\PATH\\Google-Scholar-MCP-Server\\google_scholar_server.py"
      ],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}

Using with Cline

{
  "mcpServers": {
    "google-scholar": {
      "command": "bash",
      "args": [
        "-c",
        "source /home/YOUR/PATH/.venv/bin/activate && python /home/YOUR/PATH/google_scholar_mcp_server.py"
      ],
      "env": {},
      "disabled": false,
      "autoApprove": []
    }
  }
}

🛠 MCP Tools

The Google Scholar MCP Server provides the following tools:

search_google_scholar_key_words

Search for articles on Google Scholar using key words.

Parameters:

  • query (str): Search query string
  • num_results (int, optional): Number of results to return (default: 5)

Returns: List of dictionaries containing article information

search_google_scholar_advanced

Perform an advanced search for articles on Google Scholar.

Parameters:

  • query (str): General search query
  • author (str, optional): Author name
  • year_range (tuple, optional): Tuple containing (start_year, end_year)
  • num_results (int, optional): Number of results to return (default: 5)

Returns: List of dictionaries containing article information

get_author_info

Get detailed information about an author from Google Scholar.

Parameters:

  • author_name (str): Name of the author to search for

Returns: Dictionary containing author information

📁 Project Structure

  • google_scholar_server.py: The main MCP server implementation using FastMCP
  • google_scholar_web_search.py: Contains the web scraping logic for searching Google Scholar

🔧 Dependencies

  • Python 3.10+
  • mcp[cli]>=1.4.1
  • scholarly>=1.7.0
  • asyncio>=3.4.3

You can install the required dependencies using:

pip install -r requirements.txt

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License.

⚠️ Disclaimer

This tool is for research purposes only. Please respect Google Scholar's terms of service and use this tool responsibly.

Metadata

Release files for google-scholar-mcp-server 0.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for google-scholar-mcp-server 0.1.3
File Size Uploaded
google_scholar_mcp_server-0.1.3.tar.gz 6.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for google-scholar-mcp-server 0.1.3
File Interpreter ABI Platform
google_scholar_mcp_server-0.1.3-py3-none-any.whl Python 3 none any Details

Total release size: 13.1 kB

Release files / google_scholar_mcp_server-0.1.3.tar.gz

Download URL google_scholar_mcp_server-0.1.3.tar.gz
Size 6.0 kB
Tags Source
SHA-256 checksum
How to use checksums
346feb5fc400033f93e6d472cc864397eb08ee0188502d6cf012f297639e087a
BLAKE2b-256 checksum
How to use checksums
82f6add7e108a052fefc9b05960250c67953af40ebb882a3722ca479c9609044
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.6.9

Release files / google_scholar_mcp_server-0.1.3-py3-none-any.whl

Download URL google_scholar_mcp_server-0.1.3-py3-none-any.whl
Size 7.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
473dadf8b3ef28040eb2101d984c544c8deb13d415857a322a831d2e2e5abe82
BLAKE2b-256 checksum
How to use checksums
cf94da370363a4b1be1d26827be5cc5faff99e6a4ae5baf69af0b049c1dd9375
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.6.9

Release history Release notifications | RSS feed

This release

0.1.3 This release

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page