Skip to main content
Glama
groundroof

CREHQ MCP Server

by groundroof

crehq_company_occupancy

Reconstruct the exact set of locations a brand operated on any past date, enabling historical footprint analysis and growth-curve comparisons.

Instructions

POINT-IN-TIME roster: reconstruct exactly which locations a brand operated on a given historical date. Answers 'how many units did this chain have on 2022-01-01 and where' — true historical footprint, not just today's count. Powers growth-curve and same-store analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesCREHQ company id.
dateNoISO date (YYYY-MM-DD) for the snapshot; omit for current.
limitNoMax rows (default 1000, max 10000).
offsetNoRow offset for pagination.
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the point-in-time nature and historical footprint but omits details like potential prerequisites, data accuracy, or explicit mention that it is read-only. It adds value but is not fully transparent about limitations or edge cases.

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?

The description is three sentences: a bolded core statement, a clarifying Q&A, and a use-case framing. Every sentence earns its place, and the most important information is front-loaded. No wasted words.

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 the tool's moderate complexity and full schema coverage, the description adequately explains the query's purpose and expected conceptual output ('how many units... and where') but does not specify the exact return structure. Since there is no output schema, a bit more detail could be added, but the current level is sufficient for most agents.

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 the baseline is 3. The tool description reinforces the meaning of the 'date' parameter (point-in-time snapshot) but adds no new details for 'id', 'limit', or 'offset'. It does not compensate beyond what the schema already provides.

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 clearly states a specific verb ('reconstruct'), resource ('which locations a brand operated'), and temporal scope ('given historical date'). It distinguishes itself from siblings by emphasizing 'POINT-IN-TIME' and contrasting with 'today's count', making its unique purpose immediately apparent.

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?

The description specifies when to use the tool ('given historical date', 'growth-curve and same-store analysis') and explicitly says it is 'not just today's count', which implies when not to use it. However, it does not name a specific sibling tool as an alternative, so it falls short of a 5.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/groundroof/crehq-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server