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Setup Website for AI Marketing

aipush.website.setup
Idempotent

Register a website for AI marketing. Provide domain and target URL; if DNS not configured, returns CNAME instructions. After verification, starts MIP analysis and SSL provisioning.

Instructions

Register a website for AI marketing. Call with domain + target_url. If DNS is not configured, returns DNS_NOT_VERIFIED with exact CNAME record instructions — relay to user: reference.{domain} → cname.aipush.app. After user creates DNS record, call again. On success: client registered, MIP analysis starts automatically, SSL provisioning begins. Poll website_status until mip_status='ready' and cf_hostname_status='active', then use generate_page. Idempotent (AIPush)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
website_domainYesDomain of the website to register (e.g. "example.com", "myhotel.com"). Must have a CNAME record: reference.{domain} → cname.aipush.app
target_urlYesTarget conversion URL — the single page all generated content will link to (e.g. "https://example.com/book", "https://myhotel.com/reserve"). Must be on the same domain.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.5.0
  2. Removedv1.0.20
  3. Addedv1.0.15
  4. Removedv1.0.14
  5. Addedv1.0.6
  6. Removedv1.0.5
  7. Addedv1.0.4

TDQS

A4.2/5.0
Behavior4/5

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

Discloses idempotent behavior (matches annotation), DNS_NOT_VERIFIED return, automatic MIP and SSL start. Adds context beyond annotations without contradiction.

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?

Efficient, no wasted sentences, front-loaded with action. Slightly longer due to thoroughness, but every sentence is useful.

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

Completeness5/5

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

Covers the entire setup process, including error handling (DNS not configured), retry logic, polling, and next steps (generate_page). Reference to sibling tools enhances completeness.

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% with detailed descriptions. The description restates parameters but adds no new meaning beyond what the schema provides.

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 tool registers a website for AI marketing, using specific verbs and resources. It distinguishes itself from siblings by outlining the setup workflow.

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?

Provides explicit steps: call with domain and target URL, handle DNS instructions, retry after DNS setup, poll status, then use generate_page. Lacks explicit when-not-to-use, but the workflow is clear.

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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