MCP Research Server
A Model Context Protocol server that provides tools for searching arXiv papers and managing research paper information with local storage capabilities.
README
MCP Research Server
A Model Context Protocol (MCP) server that provides tools for searching and managing research papers from arXiv.
Features
- Search Papers: Search for research papers on arXiv by topic
- Extract Paper Info: Retrieve detailed information about specific papers
- Local Storage: Automatically saves paper information to local JSON files organized by topic
Prerequisites
- Python 3.13 or higher
uvpackage manager (recommended) orpip
Installation
-
Clone or navigate to the project directory:
cd mcp_project -
Create a virtual environment:
uv venv source .venv/bin/activate # On macOS/Linux # or .venv\Scripts\activate # On Windows -
Install dependencies:
uv pip install arxiv
Running the Server
Method 1: Using MCP Inspector (Recommended for Testing)
-
Start the server with MCP Inspector:
npx @modelcontextprotocol/inspector uv run research_server.py -
Access the Inspector:
- Open your browser and go to:
http://127.0.0.1:6274 - Use the provided session token for authentication
- Open your browser and go to:
Method 2: Direct Execution
- Run the server directly:
uv run research_server.py
Available Tools
1. search_papers
Searches for papers on arXiv based on a topic and stores their information locally.
Parameters:
topic(str): The topic to search formax_results(int, optional): Maximum number of results (default: 5)
Returns: List of paper IDs found
Example:
{
"topic": "machine learning",
"max_results": 10
}
2. extract_info
Retrieves detailed information about a specific paper from local storage.
Parameters:
paper_id(str): The ID of the paper to look for
Returns: JSON string with paper information
Example:
{
"paper_id": "2301.12345"
}
Project Structure
mcp_project/
├── research_server.py # Main MCP server implementation
├── pyproject.toml # Project configuration
├── uv.lock # Dependency lock file
├── papers/ # Directory where paper data is stored
│ └── [topic_name]/ # Organized by topic
│ └── papers_info.json
└── README.md # This file
How It Works
-
Paper Search: When you search for papers, the server:
- Queries arXiv using the provided topic
- Downloads paper metadata (title, authors, summary, PDF URL, publication date)
- Saves the information to a JSON file organized by topic
- Returns the paper IDs for reference
-
Paper Retrieval: When you extract paper info, the server:
- Searches through all topic directories
- Finds the requested paper by ID
- Returns the stored information in JSON format
Data Storage
Paper information is automatically saved to the papers/ directory, organized by topic. Each topic gets its own subdirectory containing a papers_info.json file with all the papers found for that topic.
Troubleshooting
- Python Version: Ensure you're using Python 3.13 or higher
- Dependencies: Make sure all dependencies are installed with
uv pip install arxiv - Virtual Environment: Always activate the virtual environment before running the server
- Permissions: Ensure you have write permissions in the project directory for creating the
papers/folder
Development
To modify or extend the server:
- Edit
research_server.pyto add new tools or modify existing ones - Use the MCP Inspector to test your changes
- The server uses FastMCP for easy tool definition and management
License
This project is open source. Feel free to modify and distribute as needed.
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