Crawlora MCP

datasets_doordash_stores_facets

Read-only

Returns terms aggregation counts over the DoorDash store directory dataset, honoring the same filters as search. Use alongside the related search tool to discover the exact country, state, city, and tag values before filtering.

Input Schema

TableJSON Schema

Name	Required	Description
`q`	No	Optional full-text search over store name, address, city, and marketplace tags, max 256 characters.
`lat`	No	Optional latitude for radius filtering or distance sort, from -90 through 90; supply together with lon.
`lon`	No	Optional longitude for radius filtering or distance sort, from -180 through 180; supply together with lat.
`tag`	No	Optional single marketplace tag filter, e.g. Pizza or Grocery. Repeat via /doordash-stores/facets?facet=tags to discover the full tag set.
`city`	No	Optional exact city filter.
`page`	No	Offset page number, 1-based, default 1; the 10000-result window applies only to offset pagination.
`sort`	No	Optional sort order. Allowed values: relevance, rating, distance, distance_asc. Relevance ranks text matches when q is supplied and otherwise sorts by store name.
`facet`	Yes	Required facet to aggregate. Allowed values: country, state, city, tags, display_status, price_range, dash_pass_eligible.
`state`	No	Optional state/region code filter, e.g. CA.
`cursor`	No	Opaque continuation cursor returned as next_cursor. Use with pagination=cursor and the same filters and sort.
`country`	No	Optional ISO-3166-1 alpha-2 country filter, e.g. US, CA.
`radius_m`	No	Optional radius in meters, from 1 through 50000; requires lat and lon.
`max_price`	No	Optional maximum price range tier, inclusive.
`min_price`	No	Optional minimum price range tier, inclusive.
`page_size`	No	Page size, default 20, max 100; page times page_size must not exceed 10000.
`min_rating`	No	Optional minimum aggregate rating, from 0 through 5. Stores DoorDash reports with no rating are excluded.
`pagination`	No	Pagination mode: offset or cursor. Cursor mode uses a point-in-time snapshot and can enumerate beyond 10,000 results.
`dash_pass_only`	No	Optional flag; when true, keep only stores DoorDash marks DashPass eligible.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that filters match the search tool, which is useful behavioral context, but says nothing about pagination, snapshot semantics, or result shape. Adequate but thin on top of annotations.

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, no waste, with the aggregation behavior front-loaded and the usage guidance following immediately. Every 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?

Output schema exists so return values need not be described, and annotations plus a fully documented schema cover the rest. The description is complete enough for correct invocation, missing only edge-case detail like cursor versus offset behavior that the schema already handles.

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 100%, so all 18 parameters are already documented in the schema. The description adds no parameter semantics beyond the schema, so the baseline 3 applies.

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?

States a specific verb+resource (returns terms aggregation counts over the DoorDash store directory dataset) and explicitly separates itself from the search sibling by describing its aggregation role. An agent can distinguish it from datasets_doordash_stores_search and datasets_doordash_stores_item without opening a schema.

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?

Explicitly says to use it alongside the related search tool to discover exact country/state/city/tag values before filtering, which is a clear when-to-use. It refers to the search sibling only as 'the related search tool' rather than naming datasets_doordash_stores_search, so routing is slightly left to inference.

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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