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Google Scholar MCP Server

Google Scholar MCP Server

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github.com/JackKuo666Search426Updated 83w ago

About Google Scholar MCP Server

Google Scholar MCP Server is an MCP server that lets AI assistants search Google Scholar papers and retrieve their metadata. It is intended for researchers and academic users who need literature search, and it offers keyword search, advanced search and author lookup.

Key features

  1. 01Keyword search for scholarly papers
  2. 02Advanced search by author and year range
  3. 03Author information lookup
  4. 04Fast retrieval of paper metadata

Use cases

  1. 01Letting an AI assistant find papers on a given topic
  2. 02Filtering literature by author and publication years
  3. 03Looking up a researcher's Google Scholar profile

MCP support

The project is an MCP server that exposes three tools to MCP clients: search_google_scholar_key_words, search_google_scholar_advanced and get_author_info.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.