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TylerIlunga

Procore MCP Server

List All Equipment Makes

list_all_equipment_makes
Read-onlyIdempotent

Retrieve a paginated list of equipment makes for a company. Use query parameters to filter by update date and control pagination, to find IDs or get an overview of equipment makes.

Instructions

Return a list of all equipment makes. Use this to enumerate Field Productivity records when you need a paginated overview, to find IDs, or to filter by query parameters. Returns a paginated JSON array of Field Productivity records. Use page and per_page to control pagination; the response includes pagination metadata. Required parameters: company_id. Procore API: Project Management > Field Productivity. Endpoint: GET /rest/v1.0/companies/{company_id}/managed_equipment_makes

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_idYesURL path parameter — unique identifier for the company.
filters__updated_atNoQuery string parameter — return item(s) last updated within the specified ISO 8601 datetime range. Formats: `YYYY-MM-DD`...`YYYY-MM-DD` - Date `YYYY-MM-DDTHH:MM:SSZ`...`YYYY-MM-DDTHH:MM:SSZ` - DateTime with UTC Offset `YYY...
pageNoQuery string parameter — page number for paginated results (default: 1)
per_pageNoQuery string parameter — number of items per page (default: 100, max: 100)
Behavior4/5

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

Adds value beyond annotations by specifying paginated output, pagination metadata, required company_id, and endpoint. Annotations already cover safety (read-only, idempotent, non-destructive), so no contradiction.

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?

Three well-structured sentences, no fluff. Front-loaded with purpose, then usage, then details. 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?

Covers essential aspects: return type, pagination, required parameter, and endpoint. Without output schema, the description could detail the response structure more, but the paginated JSON array mention is sufficient.

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 coverage is 100%, so baseline is 3. Description mentions page/per_page for pagination and company_id as required but adds no additional meaning beyond the schema descriptions.

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?

Clearly states it returns a list of all equipment makes with a specific verb ('Return a list'). Distinguishes itself from sibling tools like show_an_equipment_make, create_an_equipment_make, etc., by focusing on enumeration and pagination.

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 describes when to use (enumerate, find IDs, filter) and provides pagination control details. Does not explicitly mention alternatives, but the context is clear given sibling tool names.

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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