Procore MCP Server

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

No annotations are provided, so the description carries full burden. It mentions 'Bulk Update' and a PATCH endpoint, implying a write operation, but doesn't disclose critical behaviors: whether it's idempotent, requires specific permissions, has rate limits, or what happens on partial failures. The HTTP method hints at mutation, but behavioral details are missing.

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

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

The description is brief and front-loaded with the core action. However, it includes extraneous details like the HTTP method and endpoint path, which are redundant for an AI agent focused on tool semantics. These could be trimmed for better conciseness, but the main purpose is stated efficiently.

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

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

Given no annotations, no output schema, and a mutation tool with 4 parameters, the description is incomplete. It lacks information on return values, error handling, prerequisites (e.g., company_id must be valid), and operational constraints. For a bulk update tool, this leaves significant gaps in understanding how to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are documented in the schema. The description adds no parameter-specific information beyond implying bulk operations on 'Managed Equipment models'. It doesn't explain how parameters interact (e.g., if 'is_active' applies to all models in bulk) or provide examples, so it meets the baseline but doesn't enhance understanding.

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

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

The description states the action ('Bulk Update') and resource ('Managed Equipment models'), but it's vague about what 'bulk update' entails—does it update multiple models at once, or update fields across models? It doesn't distinguish from sibling tools like 'bulk_update_managed_equipment_types', leaving ambiguity in scope.

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

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

No guidance on when to use this tool versus alternatives. The description includes a category tag '[Project Management/Field Productivity]' and an HTTP method 'PATCH', but these don't provide actionable usage rules or exclusions. Without explicit when/when-not instructions, the agent lacks context for selection.

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