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    Authorprofilemcp

    A Model Context Protocol (MCP) server for analyzing academic author networks and research collaborations.

    1 stars
    Python
    Updated Jun 18, 2025

    Table of Contents

    • Features
    • Installation
    • Usage
    • Running the Server
    • Example Tool Calls
    • Finding Co-authors
    • Getting Research Keywords from Google Scholar
    • Data Sources
    • Features
    • Configuration
    • Limitations
    • Contributing

    Table of Contents

    • Features
    • Installation
    • Usage
    • Running the Server
    • Example Tool Calls
    • Finding Co-authors
    • Getting Research Keywords from Google Scholar
    • Data Sources
    • Features
    • Configuration
    • Limitations
    • Contributing

    Documentation

    Academic Author Network MCP Server

    A Model Context Protocol (MCP) server for analyzing academic author networks and research collaborations.

    Features

    • get_coauthors: Find all co-authors for a given researcher
    • get_author_keywords: Extract research keywords from Google Scholar profile

    Installation

    1. Clone or download this repository

    2. Create a virtual environment:

    bash
    python -m venv venv
       source venv/bin/activate  # On Windows: venv\Scripts\activate

    3. Install dependencies:

    bash
    pip install -r requirements.txt

    Usage

    Running the Server

    bash
    python server.py

    Example Tool Calls

    Finding Co-authors

    python
    result = await get_coauthors(
        name="Yann", 
        surname="LeCun",
        institution="NYU"  # Optional
    )

    Getting Research Keywords from Google Scholar

    python
    keywords = await get_author_keywords(
        name="Yann",
        surname="LeCun"
    )

    Data Sources

    The server uses:

    • Semantic Scholar API: Primary source for author and publication data
    • OpenAlex API: Open academic knowledge graph
    • Crossref API: DOI resolution and metadata
    • Google Scholar: Web scraping for research interests and keywords

    Features

    • Rate Limiting: Respects API rate limits and includes delays for web scraping
    • Caching: Reduces redundant API calls and scraping requests
    • Error Handling: Graceful handling of API failures and scraping issues
    • Data Merging: Combines data from multiple sources for co-authors
    • Async Operations: Parallel API requests for better performance

    Configuration

    The server includes built-in rate limiting and error handling. No additional configuration is required for basic usage.

    Limitations

    • Free tier API limits apply
    • Google Scholar scraping includes respectful delays
    • Results quality depends on author name uniqueness
    • Web scraping may occasionally fail due to anti-bot measures

    Contributing

    Contributions are welcome! Please ensure all API integrations respect rate limits and terms of service.

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