uniarticles-mcp 1.1.0

Unified MCP server for multi-source academic literature retrieval

UniArticles MCP Server

中文版本 (Chinese)

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Overview

UniArticles(亿文通) is a unified academic literature retrieval server implementing the Model Context Protocol (MCP). Integrates multiple scholarly databases (Scopus, ArXiv, Semantic Scholar) into a single, standardized API for LLM agents (like Claude).

Features

• Unified Interface: Single search structure for all sources.
• Multi-Source Support:
  • Scopus: Search, abstract details, author profiles, quota check.
  • ArXiv: Search papers, search by ID, list recent papers, download PDF.
  • Semantic Scholar: Search papers.
• Standardized Returns: Consistent JSON structure (ok, source, query, count, items, error).
• Secure Configuration: API keys managed via environment variables.

⚠️ API Key Requirements

This server integrates multiple data sources, and some advanced features require API keys:

1. Elsevier API (Scopus database, Required):

   • How to get: Apply at Elsevier Developer Portal.
   • Restriction: Your institution must have a subscription to Elsevier's services; otherwise, you cannot use related functions even with an API Key.
   • Clarification: Scopus is an Elsevier database. The SCOPUS_API_KEY configured here is an Elsevier API key and may also be used for other Elsevier API services allowed by your subscription and key scope.

2. Semantic Scholar (Recommended):

   • How to get: Apply at Semantic Scholar API Key Form.
   • Restriction: Using an institutional email is recommended. Without an API Key, rate limits and results will be severely restricted.

Note: Even without the above API keys, you can still use other functions normally.

Installation & Usage

Method 1: Direct Integration with LLM Clients (Recommended)

Suitable for Cherry Studio, LM Studio, Claude Desktop, Trae, etc.

This project is published on PyPI, so you can configure it directly without downloading the full source code. Since these LLM clients are already configured with Python and uv environments, no additional downloads are required.

Simply add the following configuration to your client's MCP settings (e.g., claude_desktop_config.json):

{
  "mcpServers": {
    "uniarticles-mcp-server": {
      "command": "uvx",
      "args": [
        "--refresh", 
        "uniarticles-mcp"
      ],
      "env": {
        "SCOPUS_API_KEY": "your_elsevier_api_key_here",
        "SEMANTIC_SCHOLAR_API_KEY": "your_semantic_scholar_api_key_here"
      }
    }
  }
}

If you do not want to force refresh the cache package every time you restart, then instead add the following content: (but this will cause you to need to manually update the package when the package is updated)

{
  "mcpServers": {
    "uniarticles-mcp-server": {
      "command": "uvx",
      "args": [
        "uniarticles-mcp"
      ],
      "env": {
        "SCOPUS_API_KEY": "your_elsevier_api_key_here",
        "SEMANTIC_SCHOLAR_API_KEY": "your_semantic_scholar_api_key_here"
      }
    }
  }
}

📖 Troubleshooting? See: Step-by-Step Configuration Guide

Method 2: Local Installation (Advanced)

Requires Python 3.10+ and uv (recommended) or pip. Useful for developers or those who want to modify the source code.

Using uv:

# Clone the repository
git clone https://github.com/your-username/UniArticles_MCPserver.git
cd UniArticles_MCPserver

# Sync dependencies and run
uv sync
uv run uniarticles-mcp

Using pip:

# Clone and setup venv
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate

# Install dependencies
pip install -e .

# Run
python -m uniarticles

Configuration

Create a .env file in the project root:

SCOPUS_API_KEY=your_elsevier_api_key
SEMANTIC_SCHOLAR_API_KEY=your_semantic_scholar_api_key
ARXIV_DOWNLOAD_DIR=./arxiv_downloads

Project Structure

src/
└── uniarticles/
    ├── server.py        # MCP Server entry point
    └── sources/         # Data source modules
        ├── arxiv.py
        ├── scopus.py
        ├── semanticscholar.py
        └── ...
tests/                   # Integration and verification tests
pyproject.toml           # Project metadata and dependencies

Testing

Run automated integration tests:

python -m unittest discover tests

Verify MCP protocol handshake:

python tests/verify_server.py

Available Tools

Scopus

• search_scopus(query, count, sort): Search for documents.
• get_abstract_details(eid): Get detailed abstract information.
• get_author_profile(author_id): Get author profile information.
• get_quota_status(): Check Elsevier API quota (via Scopus endpoint).

ArXiv

• search_arxiv(query, max_results): Search papers.
• list_papers(max_results): List recent papers.
• read_paper(paper_id): Get paper metadata.
• download_paper(paper_id, filename, output_dir): Download PDF.

Semantic Scholar

• search_semantic_scholar(query, limit): Search papers.

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🤝 Call for Contributions

Due to the author's background in Chemistry, I am less familiar with databases and API developments in other research fields. I warmly welcome contributions and Pull Requests (PRs) from the community to add more data sources!

⚖️ License & Acknowledgments

License

AGPL-3.0 License with Commercial Restriction

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

🔴 Commercial Use Restriction: Commercial use of this software is permitted ONLY with explicit written authorization from the author.

Special Acknowledgments

• ScopusMCP: ScopusMCP is the first literature retrieval MCP tool the author successfully developed, but initially it was quite bloated and difficult to port.Thanks to my roommate (https://github.com/qwe4559999) for the suggestion to use pypi and uv for packaging.

• ArxivMCPserver: Integrated directly from the ArxivMCPserver project.

Special Declaration

This project uses AI-generated content.