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uber-eats-mcp-server

一个概念验证的模型上下文协议服务器，使大型语言模型应用程序能够与Uber Eats互动，允许人工智能代理通过自然语言浏览和订购食物。

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README

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

  1. Ensure you have a virtual environment activated:

    uv venv
source .venv/bin/activate  # On Unix/Mac

  2. Install required packages:

    uv pip install -r requirements.txt
playwright install

  3. Update the .env file 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
help

Runtime guide

cloud

Hosted runtime

Hosted servers run from a provider-managed environment. You usually connect the MCP client to the hosted endpoint or follow the provider's authorization flow, without keeping a local process alive

  1. Open provider connection page
  2. Authorize or copy endpoint
  3. Connect from your MCP client
terminal

Local runtime / other methods

Local servers run on your own machine or infrastructure. You normally copy the server_config into your MCP client, install the required package, and provide env variables from env_schema when needed

  1. Copy server_config
  2. Install required package
  3. Fill env variables and restart client