Provides an interface to interact with Uber Eats, likely enabling food ordering, restaurant browsing, and menu exploration capabilities through the Uber Eats platform.
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., "@Uber Eats MCP Servershow me nearby restaurants that deliver to my current location"
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.
Uber Eats MCP Server
This is a POC of how you can build an MCP servers on top of Uber Eats
https://github.com/user-attachments/assets/05efbf51-1b95-4bd2-a327-55f1fe2f958b
What is MCP?
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external tools.
Related MCP server: Uber Eats MCP Server
Prerequisites
Python 3.12 or higher
Anthropic API key or other supported LLM provider
Setup
Ensure you have a virtual environment activated:
uv venv source .venv/bin/activate # On Unix/MacInstall required packages:
uv pip install -r requirements.txt playwright installUpdate the
.envfile with your API key:ANTHROPIC_API_KEY=your_openai_api_key_here
Note
Since we're using stdio as MCP transport, we have disable all output from browser use
Debugging
You can run the MCP inspector tool with this command