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
- 01Keyword search for scholarly papers
- 02Advanced search by author and year range
- 03Author information lookup
- 04Fast retrieval of paper metadata
Use cases
- 01Letting an AI assistant find papers on a given topic
- 02Filtering literature by author and publication years
- 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.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEGoogle Scholar MCP Server
🔍 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 "{}"
-
Clone the repository:
git clone https://github.com/JackKuo666/google-scholar-MCP-Server.git cd google-scholar-MCP-Server -
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 stringnum_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 queryauthor(str, optional): Author nameyear_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 FastMCPgoogle_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
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.