A MCP Server for Google Scholar: π Enable AI assistants to search and access Google Scholar papers through a simple MCP interface.
Config is the same across clients β only the file and path differ.
{
"mcpServers": {
"google-scholar": {
"args": [
"-m",
"google_scholar_mcp_server"
],
"command": "python"
}
}
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π Enable AI assistants to search and access Google Scholar papers through a simple MCP interface.
No automated test available for this server. Check the GitHub README for setup instructions.
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π 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.
To install google-scholar Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli@latest install @JackKuo666/google-scholar-mcp-server --client claude --config "{}"
Paste the following into Settings β Cursor Settings β MCP β Add new server:
npx -y @smithery/cli@latest run @JackKuo666/google-scholar-mcp-server --client cursor --config "{}"
npx -y @smithery/cli@latest install @JackKuo666/google-scholar-mcp-server --client windsurf --config "{}"
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
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:
result = await mcp.use_tool("search_google_scholar_key_words", {
"query": "artificial intelligence ethics",
"num_results": 5
})
print(result)
result = await mcp.use_tool("search_google_scholar_advanced", {
"query": "machine learning",
"author": "Hinton",
"year_range": [2020, 2023],
"num_results": 3
})
print(result)
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.
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/YO
... [View full README on GitHub](https://github.com/JackKuo666/Google-Scholar-MCP-Server#readme)