Summary
The Uber Eats MCP Server provides a proof-of-concept integration between large language models and Uber Eats functionality through the Model Context Protocol. The server enables LLM applications to interact with Uber Eats using browser automation via Playwright, allowing users to leverage AI assistants to access food delivery capabilities programmatically. This integration solves the problem of connecting AI applications to real-world services by establishing a standardized protocol bridge between LLMs and external web-based platforms.
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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.
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/Mac -
Install required packages:
uv pip install -r requirements.txt playwright install -
Update 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
uv run mcp dev server.py
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Fastest browser for AI agents to run web automation tasks, always free.
Download Free life-time →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Connect your Claude agent to live crypto prices and trading routes via 1inch
Get the MCP →UpdatedFeb 7, 2026