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Paper Find MCP
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Paper Find MCP

An academic paper search and download server based on the Model Context Protocol (MCP), supporting multiple academic platforms such as arXiv, Semantic Scholar, PubMed, and RePEc. It provides paper retrieval, download, and reading functions for LLM tools such as Claude Desktop.
Research and dataSearch tools#Academic search#Paper download#MCP service.Python
2.5 points
9.5K
Open Site

Overview

Installation

Content Details

Alternatives

What is Paper Find MCP Server?

Paper Find MCP Server is an academic paper search tool that allows you to directly search for and download academic papers through AI assistants (such as Claude Desktop, Cursor, etc.). It integrates multiple academic databases, including arXiv, Semantic Scholar, PubMed, and RePEc in economics, enabling you to access academic resources without leaving the AI conversation interface.

How to use Paper Find MCP Server?

After installation and configuration, you can directly ask questions related to academic papers in the AI conversation. For example, you can ask the AI assistant to search for papers on specific topics, download PDF files, or even convert the paper content into readable text for analysis.

Applicable scenarios

Suitable for researchers, students, scholars, and any users who need to quickly access academic literature. Whether you are writing a paper, conducting a literature review, or keeping up with the latest research progress, this tool can help you efficiently obtain the required materials.

Main features

Multi - platform academic search
Supports one - stop search on more than 10 academic platforms such as arXiv, Semantic Scholar, PubMed, CrossRef, and Google Scholar
Professional economic search
Specifically designed for economic research, supports the RePEc/IDEAS database, and can search for working papers from institutions such as NBER, IMF, and the Federal Reserve
PDF download and reading
Supports downloading PDF files from multiple platforms and can convert PDF content into readable Markdown text
Sci - Hub integration
Can download papers behind pay - walls (literature before 2023) through Sci - Hub
Intelligent filtering and sorting
Supports sorting by relevance, time, citation count, etc., and can filter by institution, journal, and year
Advantages
One - stop search on multiple academic platforms, saving switching time
Powerful economic search function, supporting professional institutions such as NBER and IMF
Can directly obtain paper content in the AI conversation without manual operation
Supports PDF to text conversion, facilitating AI analysis of paper content
Open - source and free, with customizable configuration
Limitations
Some platforms require an API key for a better user experience
Sci - Hub only supports paper downloads before 2023
Google Scholar search is based on web scraping and may be unstable
Basic configuration steps are required for use

How to use

Install the tool
Install the paper - find - mcp package via pip or uv
Configure Claude Desktop
Edit the configuration file of Claude Desktop and add the MCP server configuration
Set environment variables (optional)
Configure the API key to increase usage limits and experience
Restart Claude Desktop
Restart the application for the configuration to take effect
Start using
Directly ask questions related to academic papers in the Claude conversation

Usage examples

Literature review assistance
When conducting a literature review on a research topic, quickly obtain the latest papers in the relevant field
Economic research
Find working papers or journal articles in a specific economic field
Paper download and reading
Obtain the full - text content of a specific paper for analysis
Cross - platform comparison
Compare research on the same topic across different academic platforms

Frequently asked questions

Is this tool free?
Do I need programming knowledge to use it?
Which AI assistants are supported?
Are there any copyright issues with the downloaded papers?
How fast is the search?
Can I search for Chinese papers?

Related resources

GitHub repository
Project source code and latest updates
MCP protocol official website
Official documentation of the Model Context Protocol
PyPI package page
Python package installation page
Chinese usage guide
Detailed Chinese usage instructions

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "paper_find_server": {
      "command": "uvx",
      "args": ["paper-find-mcp"],
      "env": {
        "SEMANTIC_SCHOLAR_API_KEY": "",
        "CROSSREF_MAILTO": "your_email@example.com",
        "NCBI_API_KEY": "",
        "PAPER_DOWNLOAD_PATH": "~/paper_downloads"
      }
    }
  }
}

{
  "mcpServers": {
    "paper_find_server": {
      "command": "paper-find-mcp",
      "args": [],
      "env": {
        "SEMANTIC_SCHOLAR_API_KEY": "",
        "CROSSREF_MAILTO": "your_email@example.com",
        "NCBI_API_KEY": "",
        "PAPER_DOWNLOAD_PATH": "~/paper_downloads"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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