mcpField
A
Arxivloader MCP Server and Client

Arxivloader MCP Server and Client

Local
github.com/alihassanmlData & Analytics1Updated 79w ago

About Arxivloader MCP Server and Client

Arxivloader MCP Server and Client is an MCP server and Streamlit client for finding arXiv research papers from queries. It displays paper titles, authors, and publication dates, and uses Groq and LangChain for query handling.

Key features

  1. 01Retrieve arXiv papers from queries
  2. 02Streamlit query and results interface
  3. 03Show titles, authors, and publication dates
  4. 04Use Groq and LangChain for query handling

Use cases

  1. 01Find research papers by topic
  2. 02Review details of retrieved papers

MCP support

The MCP server processes queries and fetches relevant papers from arXiv; the Streamlit client communicates with it over MCP and displays results.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Arxivloader MCP Server and Client

This project provides an MCP (Microservice Communication Protocol) server and client setup for fetching research papers from the arXiv. The MCP server processes queries and fetches relevant research papers, while the client communicates with the server using the MCP protocol. This project uses Streamlit for a simple UI and integrates tools such as LangChain, Groq, and MCP for communication.

Features

  • MCP Communication: Efficient communication between server and client using MCP protocol.
  • Research Paper Retrieval: Fetches research papers from arXiv based on user queries.
  • Streamlit UI: A simple web interface to input queries and display research paper results.
  • Tool Integration: Uses Groq and LangChain for enhanced query handling and processing.

Requirements

  • Python 3.8 or higher
  • streamlit
  • mcp
  • langchain
  • langchain_groq
  • dotenv
  • asyncio

You can install the required dependencies using the following:

pip install -r requirements.txt

Installation

  1. Clone this repository:
git clone https://github.com/alihassanml/Arxivloader-MCP-Server-and-Client.git
cd Arxivloader-MCP-Server-and-Client
  1. Install the necessary dependencies:
pip install -r requirements.txt
  1. Set up the .env file with any required configuration for Groq and MCP settings.

Usage

  1. Start the MCP Server:

    Run the server script to start the MCP server:

    python arxivloader.py
    
  2. Run the Client with Streamlit:

    Start the Streamlit client interface to interact with the server:

    streamlit run client.py
    
  3. Query Research Papers:

    Once the client interface is running, you can enter the name of a research paper or a query in the input field. The server will fetch relevant papers and display them.

Example

Here is an example of how the system works:

  1. The user enters a query like "Medical Claim Processing OR Health Insurance Billing" into the Streamlit interface.
  2. The MCP server processes the query and fetches relevant research paper data from arXiv.
  3. The client displays the fetched paper details, such as title, authors, and publication date.

Project Structure

.
├── arxivloader.py          # MCP server code for handling queries and fetching research papers
├── client.py               # Streamlit client UI to interact with the server
├── requirements.txt        # Python dependencies
├── .env                    # Environment variables for configuration
└── README.md               # Project documentation

Contributing

Feel free to fork this repository and contribute to the project. If you find any bugs or have feature requests, please open an issue.

License

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

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.