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AIWerk

@aiwerk/mcp-server-ghl

by AIWerk

saas_api_enable_saas_location

Enable SaaS for a GHL sub-account (location) using agency credentials. Configures V1/V2, Stripe, plans, and customer details.

Instructions

Enable SaaS for Sub-Account (Formerly Location) (requires an agency-level token, not a location PIT)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoName of the stripe customer(Required only for SaaS V1)
emailNoEmail of the stripe customer(Required only for SaaS V1)
priceIdNoRequired only while pre-configuring saas subscription
isSaaSV2YesDenotes if it is a saas v2 or v1 sub-account
companyIdYes
contactIdNoAgency subaccount used for payment provider integration(Required Only for SaaS V2)
locationIdNoDefaults to GHL_LOCATION_ID when omitted.
saasPlanIdNoRequired only while pre-configuring saas subscription
descriptionNoDescription
stripeAccountIdNoStripe account id(Required only for SaaS V1)
stripeCustomerIdNoStripe customer id if exists(Required only for SaaS V1)
providerLocationIdNoAgency Subaccount ID
Behavior4/5

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

The description adds the important constraint that an agency-level token is required, not a location PIT, which is not present in the annotations. It does not describe side effects or the exact nature of the mutation, but the annotations already indicate it is not read-only. The added auth detail enhances transparency beyond the structured data.

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 a single, well-structured sentence that front-loads the primary action and resource, then appends the crucial auth requirement. No redundant information or filler is present.

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?

The description, combined with the schema's parameter details, provides enough information for an agent to invoke the tool correctly. It could be more explicit about the distinction from bulk enable, but the singular 'Location' and the absence of 'bulk' make it reasonably clear. The auth requirement is crucial and well-stated.

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?

The schema has high description coverage (92%) and each parameter is individually described, so the description adds no additional parameter meaning. With this coverage, a baseline of 3 is appropriate; the description does not need to compensate.

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 the action ('Enable SaaS') and the target resource ('Sub-Account (Formerly Location)'), distinguishing it from bulk operations and deprecated versions by implying a single-location operation. It also includes a critical requirement (agency-level token), which adds precision beyond the name itself.

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 mentions a prerequisite (agency-level token) but does not specify when to use this tool versus alternatives like saas_api_bulk_enable_saas or the deprecated variant. No exclusions or alternative suggestions are provided, leaving usage context implicit.

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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