Skip to main content
Glama
tmedford

ubereats-order-history-mcp

by tmedford

export_ubereats_csv

Export Uber Eats order history to CSV. Choose orders, items, or transactions, filter by store or date, and get the file path and row count.

Instructions

Write orders, line items or card transactions to a CSV file (default ~/Downloads). Returns the path and row count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
storeNoOnly orders from stores whose name contains this, e.g. "home depot" or "mcdonalds" (case and symbols ignored).
end_dateNoInclusive YYYY-MM-DD.
max_pagesNoDefault 60.
start_dateNoInclusive YYYY-MM-DD.
output_pathNoFile to write. Default ~/Downloads/ubereats-<kind>-<dates>.csv

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the transparency burden. It discloses the core side effect (writing a file), the default location, and the return value (path and row count). It omits other behavioral details such as overwrite behavior, auth requirements, and pagination semantics, so it is adequate but not rich.

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 short sentences communicate purpose, default behavior, and return value with no filler. The most important information is front-loaded.

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

Completeness3/5

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

The description is reasonably complete for a 6-parameter tool whose schema covers most inputs, and it tells the agent what to expect back. However, with no annotations and no output schema, it leaves out auth, overwrite, and pagination behavior, which an agent may need to invoke it safely.

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 high at 83%, so the schema already documents most parameters. The description adds modest value by glossing 'items' as 'line items' and noting the default output location, but it does not need to repeat parameter details.

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 ('Write'), a concrete resource ('CSV file'), and the three data categories that mirror the `kind` enum. This clearly distinguishes it from the sibling get_* tools, which imply in-memory retrieval rather than file export.

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?

The usage context is implied: use when the user wants orders/items/transactions written to a CSV file. However, the description does not explicitly contrast this with get_ubereats_orders or get_ubereats_transactions, nor does it state when not to use it.

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