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Order food and manage Uber Eats deliveries with natural language.
The available material is very limited and only states that this is a proof-of-concept MCP integration for interacting with Uber Eats. It is open-source, but missing documentation and unclear maintenance/dependency status warrant caution overall; no explicit red flags justify a high-risk rating based on the provided facts.
The material explicitly states that no keys or environment variables are required, and there is no stated need for API tokens or other highly sensitive credentials. However, if it performs ordering or account actions in practice, users should still verify whether any undisclosed session-based authentication is involved.
Although the endpoint field says 'none', the stated functionality—interacting with Uber Eats for ordering and delivery management—strongly implies outbound network communication and possible transmission of user input or order-related data. The material does not disclose the actual domains, destinations, or data flow scope.
The system flags indicate that this MCP tool executes code/spawns processes, which is a standard capability for this class of tools and merits caution. The provided material does not specify what system commands, browser automation, or additional privilege boundaries are involved.
The material does not state what local files, account data, or external resources it can read or write, so the data access scope is unclear. Given its ordering/delivery use case, it may at least handle business data such as addresses, food preferences, and order details, but there is no explicit evidence of overbroad access.
A positive factor is that there is a public source repository, which provides some auditability. However, it comes from a third-party registry, lacks a README, has no declared license, shows 0 stars, and has unknown maintenance status; these factors reduce supply-chain confidence, so manual review of the repository and dependencies is advisable before use.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Uber Eats MCP Server" yet — see the docs or source repo.
Search Uber Eats for highly rated healthy lunch options nearby, keep the budget under $12 per person, prefer low-oil and high-protein meals, and recommend 3 orderable choices.
A list of matching restaurants and meal suggestions with prices, ratings, and order options.
Check the delivery status of my current Uber Eats order. If the courier is more than 20 minutes away, notify me and summarize the estimated arrival time.
The current order progress, estimated delivery time, and whether a reminder is needed.
Based on my recent Uber Eats order history, find my most frequently ordered dinner combination and help me place a similar order again.
Identification of frequent items and a reusable reorder suggestion or reorder action.
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