Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@PaperMCPFind the most-cited 2023 papers about LLM safety from US institutions."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
PaperMCP 智能学术论文检索系统
欢迎使用 PaperMCP 智能学术论文检索系统!这是一个基于 Model Context Protocol (MCP) 的高级学术论文搜索服务器,专为研究员和教授设计。通过 OpenAlex API 和智能算法,为AI助手提供精准的学术文献检索能力,大幅提升科研效率。
🌟 Features
📚 Comprehensive Paper Search
Search academic papers with flexible filtering options:
Keyword Search - Find papers by title, abstract, or full-text content
Country Filter - Limit results to papers from specific countries (CN, US, GB, etc.)
Year Filter - Search papers from specific publication years
Result Limit - Control the number of results (up to 50 papers)
Sort Options - Sort by citation count, publication date, or relevance
Open Access Filter - Find only freely accessible papers
📊 Rich Paper Information
Get comprehensive details for each paper:
Basic Info - Title, authors, publication year, document type
Abstract - Full abstract text with intelligent reconstruction from inverted index
Publication Details - Journal/venue, DOI, URLs
Citation Data - Citation count and related works
Institutional Info - Author affiliations and institutions
Subject Classification - Topics, subfields, fields, and domains
Open Access Status - OA status and APC (Article Processing Charge) information
🔍 Advanced Filtering
Institution-based Filtering - Find papers from specific countries' institutions
Temporal Filtering - Search within specific publication years
Access-based Filtering - Filter by open access availability
Quality Indicators - Sort by citation impact or publication date
🤖 MCP Integration
Seamless integration with MCP-compatible clients (like Claude) for intelligent academic research
🚦 Requirements
Before getting started, please ensure you have:
Node.js and npm:
Requires Node.js version >= 18
Download and install from nodejs.org
Email Address:
Provide a valid email address for OpenAlex API access
OpenAlex requires an email for rate limiting and contact purposes
No API key needed - OpenAlex is free to use!
🛠️ Installation & Setup
Install via Smithery (Recommended)
If you're using Claude Desktop, you can quickly install via Smithery:
Manual Installation
Get the code:
git clone https://github.com/guangxiangdebizi/PaperMCP.git cd PaperMCPInstall dependencies:
npm installConfigure Email Address:
Create a
.envfile in the project root directoryAdd the following content:
OPENALEX_EMAIL=your_email@example.comOr set it directly in the
src/config.tsfile
Build the project:
npm run build
🚀 Running the Server
There are two ways to start the server:
Method 1: Using stdio mode (Direct run)
Method 2: Using Supergateway (Recommended for development)
📝 Configuring MCP Clients
To use this server in Claude or other MCP clients, you need the following configuration:
Claude Configuration
Add the following to Claude's configuration file:
If using stdio mode directly (without Supergateway), configure as follows:
💡 Usage Examples
Here are some example queries using the PaperMCP server:
1. Basic Paper Search
You can ask Claude:
General Search:
"Search for papers about machine learning published in 2024"
Country-specific Search:
"Find papers about artificial intelligence from Chinese institutions in 2023"
Author/Institution Focus:
"Search for papers about LLM from US universities in the last 2 years"
2. Advanced Filtering
Citation-based Search:
"Find the most-cited papers about deep learning from 2022, limited to 20 results"
Open Access Papers:
"Search for open access papers about natural language processing from 2024"
Specific Year Range:
"Find papers about computer vision published in 2023, sorted by citation count"
3. Research-focused Queries
Literature Review:
"Help me find recent papers about transformer architectures for my literature review"
Trend Analysis:
"Search for papers about quantum computing from different countries to analyze research trends"
Interdisciplinary Research:
"Find papers that combine AI and biology, focusing on recent publications"
4. Complex Research Queries
Comparative Analysis:
"Compare recent AI research output between China and the US by finding papers from both countries in 2024"
Field Evolution:
"Show me how research in reinforcement learning has evolved by finding papers from 2020-2024"
Open Science Focus:
"Find highly-cited open access papers in machine learning to understand accessible research trends"
This will use the paper_search tool to retrieve comprehensive academic paper information.
📊 Supported Search Parameters
The PaperMCP server supports the following search parameters:
Parameter | Type | Description | Example |
| string | Search keywords (required) | "machine learning", "deep learning" |
| string | Filter by country code | "CN" (China), "US" (USA), "GB" (UK) |
| number | Filter by publication year | 2024, 2023 |
| number | Number of results (max 50) | 10, 20, 50 |
| string | Sort method | "cited_by_count", "publication_date", "relevance_score" |
| boolean | Filter open access papers | true, false |
📈 Data Sources
This server uses the OpenAlex API, which provides:
260M+ papers from across all disciplines
Real-time updates with new publications
Comprehensive metadata including citations, authors, institutions
Open access information and APC data
Subject classification at multiple levels
Institution and country data for geographic analysis
🔮 Future Plans
Future enhancements may include:
Author Search - Find papers by specific authors
Institution Search - Search within specific institutions
Journal/Venue Filtering - Filter by publication venue
Citation Network Analysis - Explore citation relationships
Concept-based Search - Search by research concepts and topics
Export Functionality - Export results in various formats (BibTeX, etc.)
📄 License
This project is licensed under the MIT License. See the LICENSE file for details.
👨💻 Author
Name: Xingyu_Chen
Email: guangxiangdebizi@gmail.com
GitHub: guangxiangdebizi
🙏 Acknowledgments
This project uses the OpenAlex API, a free and open catalog of scholarly papers, authors, institutions, and more. Special thanks to the OpenAlex team for providing this invaluable resource to the research community.