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licenseNot graded
qualityD
maintenanceA proof-of-concept server implementing the Model Context Protocol that enables LLM applications to interact with Uber Eats functionality.
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Uber Eats MCP Server
by iflow-mcp
Provides tools for interacting with Uber Eats, enabling AI agents to browse menus, place orders, and manage deliveries through the Uber Eats platform.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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.
Related MCP server: Uber Eats MCP Server
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/MacInstall required packages:
uv pip install -r requirements.txt playwright installUpdate 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.pyTool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
This server cannot be deployed
Maintenance
ActivityInactive
ResponsivenessNo recent community issues
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