What is Google Scholar Mcp

google_scholar_mcp is an MCP-based service that provides an optimized search for academic papers on Google Scholar, specifically designed to work seamlessly with Cherry Studio.

Use cases

Use cases include conducting literature reviews, retrieving specific academic papers, and integrating scholarly search capabilities into research workflows.

How to use

To use google_scholar_mcp, install the package using ‘uv’, configure Cherry Studio with the provided MCP server settings, and run the server to start retrieving academic paper abstracts.

Key features

Key features include the ability to search academic papers, automatically retrieve and filter complete abstracts, support for Chinese keyword searches with auto-translation, and comprehensive metadata retrieval.

Where to use

google_scholar_mcp is useful in academic research, educational institutions, and any field requiring access to scholarly articles and research papers.

Google Scholar MCP Server (Optimized for Cherry Studio)

An MCP-based Google Scholar search service optimized for Cherry Studio, providing academic paper search, abstract retrieval, and supporting both Chinese and English queries.

Features

• Search academic papers via Google Scholar (not limited to arXiv)
• Automatically retrieve and filter paper abstracts (only keeping complete abstracts)
• Support Chinese keyword search with auto-translation to English
• Return comprehensive paper metadata (title, authors, journal, year, citations, URL, etc.)
• Optimized for Cherry Studio integration via MCP protocol

Installation

google_scholar_mcp can be installed using uv. Below are two approaches: a quick start for immediate use and a detailed setup for development.

Quick Start

For users who want to quickly run the server:

1. Install Package:

   uv add google_scholar_mcp
   

2. Configure Cherry Studio:
   Add this configuration to your Cherry Studio configuration file:

   {
     "mcpServers": {
       "google_scholar_server": {
         "command": "uv",
         "args": [
           "--directory",
           "/path/to/your/google_scholar_mcp",
           "run",
           "gsd_mcp.py"
         ]
       }
     }
   }
   

   Note: Replace /path/to/your/google_scholar_mcp with your actual installation path.

Usage

Response Example

=== Paper 1 ===
Title: Deep Learning
Authors: Yann LeCun, Yoshua Bengio, Geoffrey Hinton  
Journal: Nature
Year: 2015
URL: https://www.nature.com/articles/nature14539
Citations: 95183
Abstract:
  Deep learning allows computational models composed of multiple processing layers to learn representations of data with multiple levels of abstraction...

Notes

1. Abstract retrieval depends on paper page structure and may not always succeed
2. VPN connection is required throughout usage to access Google Scholar
3. Please set reasonable request frequency to avoid being blocked by Google Scholar
4. Chinese queries are automatically translated to English for searching

Dependencies

• googletrans>=4.0.2
• httpx>=0.28.1
• mcp[cli]>=1.7.0
• scholarly>=1.7.11

License

MIT License