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Sdfsdf MCP Server

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Find academic papers across major sources like arXiv, PubMed, bioRxiv, and more. Download PDFs whe…

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Find academic papers across major sources like arXiv, PubMed, bioRxiv, and more. Download PDFs whe…

Remote endpoints: streamable-http: https://server.smithery.ai/@morosss/sdfsdf/mcp

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

5 files analyzed · No issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Install & Connect

Available as Local & Remote

This plugin can run on your machine or connect to a hosted endpoint. during install.

Documentation

View on GitHub

From the project's GitHub README.

Paper Search MCP

A Model Context Protocol (MCP) server for searching and downloading academic papers from multiple sources, including arXiv, PubMed, bioRxiv, and Sci-Hub (optional). Designed for seamless integration with large language models like Claude Desktop.

PyPI License Python smithery badge


Table of Contents


Overview

paper-search-mcp is a Python-based MCP server that enables users to search and download academic papers from various platforms. It provides tools for searching papers (e.g., search_arxiv) and downloading PDFs (e.g., download_arxiv), making it ideal for researchers and AI-driven workflows. Built with the MCP Python SDK, it integrates seamlessly with LLM clients like Claude Desktop.


Features

  • Multi-Source Support: Search and download papers from arXiv, PubMed, bioRxiv, medRxiv, Google Scholar, IACR ePrint Archive, Semantic Scholar.
  • Standardized Output: Papers are returned in a consistent dictionary format via the Paper class.
  • Asynchronous Tools: Efficiently handles network requests using httpx.
  • MCP Integration: Compatible with MCP clients for LLM context enhancement.
  • Extensible Design: Easily add new academic platforms by extending the academic_platforms module.

Installation

paper-search-mcp can be installed using uv or pip. Below are two approaches: a quick start for immediate use and a detailed setup for development.

Installing via Smithery

To install paper-search-mcp for Claude Desktop automatically via Smithery:

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

Quick Start

For users who want to quickly run the server:

  1. Install Package:

    uv add paper-search-mcp
    
  2. Configure Claude Desktop: Add this configuration to ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

    {
      "mcpServers": {
        "paper_search_server": {
          "command": "uv",
          "args": [
            "run",
            "--directory",
            "/path/to/your/paper-search-mcp",
            "-m",
            "paper_search_mcp.server"
          ],
          "env": {
            "SEMANTIC_SCHOLAR_API_KEY": "" // Optional: For enhanced Semantic Scholar features
          }
        }
      }
    }
    

    Note: Replace /path/to/your/paper-search-mcp with your actual installation path.

For Development

For developers who want to modify the code or contribute:

  1. Setup Environment:

    # Install uv if not installed
    curl -LsSf https://astral.sh/uv/install.sh | sh
    
    # Clone repository
    git clone https://github.com/openags/paper-search-mcp.git
    cd paper-search-mcp
    
    # Create and activate virtual environment
    uv venv
    source .venv/bin/activate  # On Windows: .venv\Scripts\activate
    
  2. Install Dependencies:

    # Install project in editable mode
    uv add -e .
    
    # Add development dependencies (optional)
    uv add pytest flake8
    

Contributing

We welcome contributions! Here's how to get started:

  1. Fork the Repository: Click "Fork" on GitHub.

  2. Clone and Set Up:

    git clone https://github.com/yourusername/paper-search-mcp.git
    cd paper-search-mcp
    pip install -e ".[dev]"  # Install dev dependencies (if added to pyproject.toml)
    
  3. Make Changes:

    • Add new platforms in academic_platforms/.
    • Update tests in tests/.
  4. Submit a Pull Request: Push changes and create a PR on GitHub.


Demo

TODO

Planned Academic Platforms

  • [√] arXiv
  • [√] PubMed
  • [√] bioRxiv
  • [√] medRxiv
  • [√] Google Scholar
  • [√] IACR ePrint Archive
  • [√] Semantic Scholar
  • PubMed Central (PMC)
  • Science Direct
  • Springer Link
  • IEEE Xplore
  • ACM Digital Library
  • Web of Science
  • Scopus
  • JSTOR
  • ResearchGate
  • CORE
  • Microsoft Academic

License

This project is licensed under the MIT License. See the LICENSE file for details.


Happy researching with paper-search-mcp! If you encounter issues, open a GitHub issue.

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Sdfsdf MCP Server - Find academic papers across major sources like arXiv, | MCP Marketplace