Uber Eats Mcp Server
What is Uber Eats Mcp Server
The uber-eats-mcp-server is a proof of concept (POC) demonstrating how to build an MCP server utilizing the Uber Eats platform, leveraging the Model Context Protocol (MCP) for seamless integration with large language model (LLM) applications.
Use cases
Use cases for the uber-eats-mcp-server include developing applications that require real-time data from Uber Eats, creating chatbots that can interact with users about food delivery, and integrating LLM capabilities into food service applications.
How to use
To use the uber-eats-mcp-server, first ensure you have Python 3.12 or higher and an API key from Anthropic or another supported LLM provider. Set up a virtual environment, install the required packages, and update the .env file with your API key. You can then run the MCP inspector tool for debugging.
Key features
Key features include seamless integration with LLM applications, support for the Model Context Protocol, and a debugging tool for inspecting MCP operations.
Where to use
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Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Uber Eats Mcp Server
The uber-eats-mcp-server is a proof of concept (POC) demonstrating how to build an MCP server utilizing the Uber Eats platform, leveraging the Model Context Protocol (MCP) for seamless integration with large language model (LLM) applications.
Use cases
Use cases for the uber-eats-mcp-server include developing applications that require real-time data from Uber Eats, creating chatbots that can interact with users about food delivery, and integrating LLM capabilities into food service applications.
How to use
To use the uber-eats-mcp-server, first ensure you have Python 3.12 or higher and an API key from Anthropic or another supported LLM provider. Set up a virtual environment, install the required packages, and update the .env file with your API key. You can then run the MCP inspector tool for debugging.
Key features
Key features include seamless integration with LLM applications, support for the Model Context Protocol, and a debugging tool for inspecting MCP operations.
Where to use
undefined
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
