Allows searching for papers on arXiv and extracting specific paper information, enabling access to scientific research content and metadata
Provides CI/CD workflow integration with linting and test capabilities that run automatically on push or pull requests to the main branch
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Model Context Protocol Python Serversearch for recent papers about large language models"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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Model Context Protocol (MCP) Python Server
This repository provides a sample implementation of a Model Context Protocol (MCP) server in Python.
Features
Search for papers on arXiv and store their information
Extract information about a specific paper
Ready for extension with more MCP tools
Related MCP server: ArXiv-MCP
Getting Started
1. Clone the repository
git clone <your-repo-url>
cd MCP_Python2. Create and activate a virtual environment
python3 -m venv venv
source venv/bin/activate3. Install dependencies
pip install arxiv4. Run the server
python mcp_server/server.pyGitHub Actions CI
On every push or pull request to
main, the workflow runs linting and (placeholder) tests.Add your tests in the
tests/directory.
Project Structure
mcp_server/
server.py # MCP server implementation
.github/
workflows/ci.yml # GitHub Actions workflow
README.mdReferences
Replace <your-repo-url> with your actual repository URL after pushing to GitHub.
mcp_python
88aa9b0e1bcd2704e4fbb53f41ca4a158b4d35c8
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