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TylerIlunga

Procore MCP Server

Update Material

update_material

Update a specified material in Field Productivity. Supply the material ID and project ID to modify only the provided fields.

Instructions

Update a specified Material. Use this to update an existing Field Productivity records (only the supplied fields are changed). Updates the specified Field Productivity records and returns the modified object on success. Required parameters: id, project_id. Procore API: Project Management > Field Productivity. Endpoint: PATCH /rest/v1.0/projects/{project_id}/materials/{id}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesURL path parameter — unique identifier of the Field Productivity resource
project_idYesURL path parameter — unique identifier for the project.
time_and_material_entry_idNoJSON request body field — time & Material Entry Id the material is associated with
nameNoJSON request body field — name of the material
descriptionNoJSON request body field — description of the material
uomNoJSON request body field — unit of measure for the material
quantityNoJSON request body field — quantity of the material
Behavior3/5

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

The description mentions that 'only the supplied fields are changed' (partial update) and that it 'returns the modified object on success.' Annotations already indicate the tool is not read-only and not destructive, so the description adds moderate value (partial update info) but lacks details on side effects or auth requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loading the purpose and usage. It includes required params and API endpoint without extraneous text. Minor repetition ('Field Productivity records') but overall efficient.

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 absence of an output schema, the description states it returns the modified object. It also provides the API context (Procore API, endpoint URL). For a mutation tool with 7 parameters and clear schema, this is fairly complete, though error handling or rate limits are omitted.

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?

Input schema has 100% coverage, so description adds limited parameter meaning beyond the schema. It highlights required parameters (id, project_id) and implies body fields are optional, but does not elaborate on their syntax or constraints beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool updates a specified Material, linking it to Field Productivity records. It uses specific verb ('Update') and resource ('Material'), but could more explicitly differentiate from other update tools in the extensive sibling list.

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

Usage Guidelines2/5

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

The description says 'Use this to update an existing Field Productivity records' but provides no guidance on when not to use or alternatives. With many update siblings on the server, this lack of contextual usage advice is a significant gap.

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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