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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

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:

  1. Node.js and npm:

    • Requires Node.js version >= 18

    • Download and install from nodejs.org

  2. 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

If you're using Claude Desktop, you can quickly install via Smithery:

npx -y @smithery/cli install @guangxiangdebizi/paper-mcp --client claude

Manual Installation

  1. Get the code:

    git clone https://github.com/guangxiangdebizi/PaperMCP.git cd PaperMCP
  2. Install dependencies:

    npm install
  3. Configure Email Address:

    • Create a .env file in the project root directory

    • Add the following content:

      OPENALEX_EMAIL=your_email@example.com
    • Or set it directly in the src/config.ts file

  4. Build the project:

    npm run build

🚀 Running the Server

There are two ways to start the server:

Method 1: Using stdio mode (Direct run)

node build/index.js
npx supergateway --stdio "node build/index.js" --port 3100

📝 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:

{ "mcpServers": { "paper-search-server": { "url": "http://localhost:3100/sse", // If using Supergateway "type": "sse", "disabled": false, "autoApprove": [ "paper_search" ] } } }

If using stdio mode directly (without Supergateway), configure as follows:

{ "mcpServers": { "paper-search-server": { "command": "C:/path/to/PaperMCP/build/index.js", // Modify to actual path "type": "stdio", "disabled": false, "autoApprove": [ "paper_search" ] } } }

💡 Usage Examples

Here are some example queries using the PaperMCP server:

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

query

string

Search keywords (required)

"machine learning", "deep learning"

country_code

string

Filter by country code

"CN" (China), "US" (USA), "GB" (UK)

year

number

Filter by publication year

2024, 2023

num_results

number

Number of results (max 50)

10, 20, 50

sort_by

string

Sort method

"cited_by_count", "publication_date", "relevance_score"

open_access

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:

  1. Author Search - Find papers by specific authors

  2. Institution Search - Search within specific institutions

  3. Journal/Venue Filtering - Filter by publication venue

  4. Citation Network Analysis - Explore citation relationships

  5. Concept-based Search - Search by research concepts and topics

  6. 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

🙏 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.

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security - not tested
A
license - permissive license
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quality - not tested

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