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 "Deploy 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 Server search 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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This repository provides a sample implementation of a Model Context Protocol (MCP) server in Python.
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 Server
git clone <your-repo-url>
cd MCP_Pythonpython3 -m venv venv
source venv/bin/activatepip install arxivpython mcp_server/server.pyOn every push or pull request to main, the workflow runs linting and (placeholder) tests.
Add your tests in the tests/ directory.
mcp_server/
server.py # MCP server implementation
.github/
workflows/ci.yml # GitHub Actions workflow
README.md<your-repo-url> with your actual repository URL after pushing to GitHub.88aa9b0e1bcd2704e4fbb53f41ca4a158b4d35c8
This server cannot be deployed
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
The Mercado Pago MCP Server implements the Model Context Protocol to provide AI agents and LLMs with access to Mercado Pago's APIs and tools within compatible development environments. It acts as an intermediary that translates Mercado Pago resources into executable functions (tools) that AI applications can invoke to perform actions and automate flows. The server simplifies integration, enables using documentation to implement or improve code, and optimizes operations through natural language interactions without manual implementations.
Search GitHub, npm, PyPI, StackOverflow, ArXiv from one MCP — built for coding agents.
