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@striderlabs/mcp-ubereats

@striderlabs/mcp-ubereats

by markswendsen-code
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

ubereats_search

Search restaurants on Uber Eats by name, food type, or cuisine. Returns matching restaurants with delivery information.

Instructions

Search for restaurants on Uber Eats. Can search by restaurant name, food type, or cuisine. Returns a list of matching restaurants with delivery info.

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": {
      "query": "<query>"
    },
    "name": "ubereats_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesSearch query - restaurant name, food type, or dish (e.g., 'pizza', 'sushi', 'Chipotle')
cuisineNoFilter by cuisine type (e.g., 'italian', 'chinese', 'mexican', 'american')

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 provided, but description states it returns a list with delivery info, adding behavioral context beyond basic search. However, lacks details on side effects or rate limits.

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?

Two sentences, front-loaded with key purpose, no redundant or extraneous information.

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?

Given no output schema, description mentions return includes delivery info, which is helpful. With 2 parameters and simple behavior, it's largely complete, though more detail on output structure would improve.

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

Parameters4/5

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

Schema coverage is 100% for both parameters with clear descriptions. The description adds value by explaining the query parameter can be restaurant name, food type, or dish, supplementing schema.

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?

Description uses specific verb 'Search for restaurants on Uber Eats' and lists search methods (name, food type, cuisine), clearly distinguishing from siblings like 'ubereats_get_restaurant'.

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

Usage Guidelines3/5

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

Implied usage is clear (search for restaurants), but no explicit when-not-to-use or comparison with siblings like 'ubereats_get_restaurant' for specific restaurant details.

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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