Uber Eats
About
Integrates with Uber Eats using browser automation to enable restaurant searches, menu exploration, and food order placement for applications requiring food delivery capabilities.
Details
- Author
- ericzakariasson
- Repository
- ericzakariasson/uber-eats-mcp-server
- GitHub stars
- 156
- Downloads
- 405
- Categories
- Productivity, Developer Tools, Design, AI, Search, Frontend, API, Infrastructure, Other
- Tags
- #web
Jump to
- Proof-of-concept integration with Uber Eats via MCP.
- Uses Playwright for browser automation.
- Supports stdio MCP transport.
- Works with Anthropic API or other supported LLM providers.
- Runs locally with minimal setup.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Uber EatsCommand (node, npx, python, etc.)npxArguments-
Argument 1
-y -
Argument 2
@highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Set up a Python virtual environment (Python 3.12+), install dependencies with uv pip install -r requirements.txt, run playwright install, then configure your LLM API key (e.g., ANTHROPIC_API_KEY) in the .env file. Use uv run mcp dev server.py to start the server with the MCP inspector for debugging.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"uber eats": {
"env": {},
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
}
}Linux
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Macos
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Windows
{
"env": [],
"args": [
"/c",
"npx",
"-y",
"@highlight/mcp-server"
],
"command": "cmd"
}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
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