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Uber Eats MCP Server

Uber Eats MCP Server

by matiasconcha11
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

uber_eats_set_checkout_tip

Set the delivery tip percentage on a draft Uber Eats order using the checkout preview's draft order UUID. Specify a tip percent (0, 5, 10, 15, or 20) to update the tip before finalizing the order.

Instructions

Set the delivery tip on the current draft order (API). Use tip values that match
Uber's buttons: typically 0, 5, 10, 15, or 20. Call uber_eats_checkout_preview
first and pass draft_order_uuid from the response.

Args:
    draft_order_uuid: Draft order UUID from checkout preview
    tip_percent: Tip percentage (e.g. 10 for 10%)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "draft_order_uuid": "<draft_order_uuid>",
      "tip_percent": "<tip_percent>"
    },
    "name": "uber_eats_set_checkout_tip"
  }
}

Input Schema

NameRequiredDescriptionDefault
tip_percentYes
draft_order_uuidYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It implies mutation (setting a tip) which is a write operation, and specifies it affects 'the current draft order' - a useful scoping detail. However, it doesn't disclose error conditions (e.g., what happens if called without a prior preview), reversibility, or whether it's idempotent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is tightly constructed with a clear purpose line, usage prerequisite, and parameter breakdown. No wasted words; each sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and only 2 parameters, the description covers the prerequisite call chain and parameter semantics well. Minor gaps include no mention of edge cases (e.g., applying tip to a non-delivery order) or confirmation behavior, but overall adequate for a focused mutation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It clarifies tip_percent as 'e.g. 10 for 10%' and defines draft_order_uuid as 'from checkout preview', which adds meaning beyond bare parameter names. However, it doesn't specify bounds/valid range for tip_percent beyond the button examples, nor whether fractional percentages are allowed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource ('Set the delivery tip on the current draft order') which clearly distinguishes it from siblings like set_checkout_payment or uber_eats_checkout_preview. It also notes the 'API' context which distinguishes this action from UI-based interactions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance to call uber_eats_checkout_preview first and pass the draft_order_uuid from its response, establishing the prerequisite sequence. It also gives concrete tip value examples (0, 5, 10, 15, 20) matching Uber's buttons, but doesn't explicitly say when NOT to use it versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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