Uber Eats MCP Server logo

Uber Eats MCP Server

by MCP-Mirror

This is a proof-of-concept (POC) server demonstrating how to build an MCP server on top of Uber Eats. It leverages the Model Context Protocol for integration with LLM applications.

View on GitHub

Last updated: N/A

What is Uber Eats MCP Server?

This is a POC MCP server built on top of Uber Eats, utilizing the Model Context Protocol to enable seamless integration between LLM applications and external tools.

How to use Uber Eats MCP Server?

To use this server, you need Python 3.12 or higher and an Anthropic API key (or other supported LLM provider). First, set up a virtual environment and install the required packages from requirements.txt. Then, update the .env file with your API key. Finally, you can run the server using the command uv run mcp dev server.py.

Key features of Uber Eats MCP Server

  • MCP Integration

  • Uber Eats API interaction (simulated)

  • Python implementation

  • Stdio MCP transport

Use cases of Uber Eats MCP Server

  • Integrating Uber Eats data into LLM applications

  • Building conversational interfaces for Uber Eats

  • Automating Uber Eats tasks with LLMs

  • Creating custom Uber Eats workflows with LLMs

FAQ from Uber Eats MCP Server

What is MCP?

The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external tools.

What are the prerequisites?

Python 3.12 or higher and an Anthropic API key (or other supported LLM provider).

How do I install the dependencies?

Use uv pip install -r requirements.txt and playwright install.

How do I set up the API key?

Update the .env file with your API key: ANTHROPIC_API_KEY=your_openai_api_key_here.

How do I run the server?

Use the command uv run mcp dev server.py.