🚀 ArxivSearcher MCP Server

An MCP server for intelligently searching Software Engineering papers on arXiv, with advanced filtering and sorting.

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📋 Prerequisites

Before you begin, make sure you have installed:

• Python (3.11 or higher)
• uv (a fast Python package installer and resolver)
• Node.js and npm (for debugging with the MCP Inspector)

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⚡️ Quickstart in VS Code

Follow these steps to get the server running in your workspace:

1. Create .vscode/mcp.json: In your project root, create the .vscode folder if it doesn't exist. Inside, create a file named mcp.json.

2. Add the server configuration: Copy and paste the following configuration into .vscode/mcp.json so VS Code knows how to run the server.

   {
     "servers": {
         "arxiv-search": {
             "command": "uv",
             "args": [
                 "run",
                 "${workspaceFolder}/arxiv_searcher/arxiv_mcp.py"
             ]
         }
     }
   }
   

3. Start the server

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✨ Features

🛠️ Tools Provided

This MCP server exposes several useful tools for searching, analyzing, and exporting arXiv papers in the field of software engineering:

search_papers

Searches arXiv papers filtered by the Software Engineering category (cs.SE).

• Parameters: query, max_results, start_date, end_date, sort_by_relevance, category
• Returns: Dictionary with the query used and the results.

get_paper_details

Gets detailed information about a paper by its arXiv ID.

• Parameters: arxiv_id
• Returns: Title, authors, abstract, dates, categories, DOI, etc.

search_by_author

Searches for papers by a specific author, with optional category and date filters.

• Parameters: author_name, max_results, category, start_date, end_date
• Returns: List of found papers.

analyze_paper_trends

Analyzes trends in a collection of papers (authors, keywords, timeline, categories).

• Parameters: papers, analysis_type
• Returns: Statistics and analysis according to the requested type.

find_related_papers

Finds related papers based on the title of a reference paper, using keyword similarity.

• Parameters: paper_title, max_results, similarity_threshold, category
• Returns: List of similar papers.

download_paper_pdf

Downloads the PDF of an arXiv paper.

• Parameters: pdf_url, save_path, filename
• Returns: Path and status of the download.

export_search_results

Exports search results to various formats (bibtex, csv, json, markdown).

• Parameters: results, format, filename, save_path
• Returns: Path to the exported file and a preview of the content.

get_arxiv_categories

Returns the list of arXiv categories and their descriptions.

• Parameters: None
• Returns: Dictionary of categories and usage notes.

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🧑‍💻 Example Usage

Here's how you can call the tool from a compatible MCP client:

@arxiv-search.search_papers(query="secure software development lifecycle from 2022", max_results=5)

This will search for the 5 most relevant papers since 2022 in the software engineering category.

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🛠️ Development

📦 Install dependencies

Set up your virtual environment and install the required packages:

uv sync

▶️ Run for development

Start the server directly from your terminal:

uv run --directory src/arxivsearcher/ arxiv_mcp.py

🐞 Debugging

For an interactive debugging experience, use the MCP Inspector:

# Option 1: Using MCP Inspector
npx @modelcontextprotocol/inspector uv run --directory arxiv_searcher/arxiv_mcp.py

# Option 2: Using fastmcp CLI
fastmcp dev arxiv_searcher/arxiv_mcp.py

When launched, the Inspector will provide a URL to view and debug server communications in your browser. Don't forget to copy the session token!

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👤 Author

Developed by emi-dm.

💡 Contributions and improvements are welcome! Feel free to open a Pull Request (PR) if you have suggestions or enhancements.

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📚 License

This project is licensed under the MIT License.