About
Google Scholar Search Server enables AI assistants to search Google Scholar for academic papers and scholarly research through a streaming HTTP interface. Key features: - Search Google Scholar for academic papers, research articles, and scholarly publications - Returns structured search results with paper details and metadata - Real-time streaming via Server-Sent Events (SSE) for live result updates - Multi-session support for handling simultaneous client connections - Integrates with AI models like Google Gemini for enhanced research workflows
Tools 1
search_google_scholarSearch Google Scholar for academic papers and research articles. Supports filtering by author, publication year range, and returns structured results with titles, authors, abstracts, and URLs.
README
Google Scholar MCP Server
[](https://smithery.ai/server/@mochow13/google-scholar-mcp)
A Model Context Protocol (MCP) server that provides Google Scholar search capabilities through a streamable HTTP transport. This project demonstrates how to build an MCP server with custom tools and integrate it with AI models like Google's Gemini.
Overview
This project consists of two main components:
Architecture
MCP Server Implementation
The server is built using the @modelcontextprotocol/sdk and implements:
Available Tools
The server currently provides one main tool:
#### search_google_scholar
Transport Protocol
The server uses StreamableHTTPServerTransport which supports:
Smithery
The server is now available in Smithery: Google Scholar Search Server
Installation
Installing via Smithery
To install google-scholar-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @mochow13/google-scholar-mcp --client claude
1. Clone the repository:
git clone
cd google-scholar-mcp
2. Install and build:
cd server
npm install
npm run buildcd client
npm install
npm run build
Running the Server
1. Start the MCP server:
cd server
node build/index.js
The server will start on port 3000 and provide the following endpoints:
POST /mcp - Main MCP communication endpointGET /mcp - SSE stream endpoint for real-time updatesServer Features
Running the Client
The client demonstrates how to integrate the MCP server with Google's Gemini AI model.
1. Ensure you have a valid GEMINI_API_KEY and provide it with ``export GEMINI_API_KEY=
bash
cd client
node build/index.js
2. Start the client:
3. The client will connect to the server and start an interactive chat loop
Client Features
#### Conversation Management
#### AI Integration
#### Interactive Features
Usage Example
Query: Find recent papers about machine learning in healthcare
[Called tool search_google_scholar with args {"query":"machine learning healthcare recent"}]
Based on the search results, here are some recent papers about machine learning in healthcare:
1. "Deep Learning Applications in Medical Imaging" - This paper explores... 2. "Predictive Analytics in Patient Care" - Research on using ML for... ...
Query: What about specifically for diagnostic imaging?
[Called tool search_google_scholar with args {"query":"machine learning diagnostic imaging healthcare"}]
Here are papers specifically focused on diagnostic imaging applications: ...
Development
Project Structure
Key Components
#### MCPServer Class (
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