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ghl-mcp-server-v2

by zackscriven

ghl_object_create_record

Create a record for any custom or standard object in GoHighLevel. Provide the schema key and a body with the object's property values.

Instructions

SPEC GAP: CreateCustomObjectRecordDto is an empty object schema in v3/objects-v3.json — verified against the raw spec, not an extraction bug. The body property will accept arbitrary JSON; GHL's convention (per external docs linked from this op, not confirmed in this corpus) is a properties object keyed by the object's field keys. Create Record Create a Custom Object Record. Supported Objects business and custom objects. Documentation Link - https://doc.clickup.com/8631005/d/h/87cpx-277156/93bf0c2e23177b0/87cpx-376296 Endpoint: POST /objects/{schemaKey}/records (Version header: v3; source: v3/objects-v3.json) OAuth scopes: objects/record.write

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesRequest body (schema carried verbatim from the official OpenAPI spec).
schemaKeyYesThe key of the Custom Object / Standard Object Schema. For custom objects, the key must include the “custom_objects.” prefix, while standard objects use their respective object keys. This information is available on the Custom Objects Details page under Settings.
Behavior3/5

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

Annotations provide readOnlyHint=false, destructiveHint=false, openWorldHint=true. The description adds useful context: body accepts arbitrary JSON (convention of 'properties' object) and OAuth scopes (objects/record.write). But the confusing spec gap note detracts, and no mention of idempotency or response behavior.

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

Conciseness2/5

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

The description includes a verbose 'SPEC GAP' paragraph that is irrelevant for an AI agent. The useful part is relatively short, but the extraneous information harms conciseness and structure.

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

Completeness3/5

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

For a creation tool with 2 params and no output schema, the description covers body flexibility and schemaKey prefix but lacks return format, error handling, or examples of when creation might fail. The spec gap note adds confusion rather than completeness.

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

Parameters4/5

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

Both parameters have schema descriptions (100% coverage). The description adds value: for 'body', it explains arbitrary JSON and the expected 'properties' structure; for 'schemaKey', it details prefix requirements and examples beyond the schema.

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 states 'Create a Custom Object Record' and mentions supported objects (business and custom objects), clearly indicating the action and resource. However, the initial 'SPEC GAP' text and note about empty schema are distracting and reduce clarity slightly.

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?

No explicit guidance on when to use this tool versus alternatives like ghl_object_update_record or ghl_object_get_record_by_id. The description does not differentiate based on use case or prerequisites.

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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