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raihan675

OpenAI Ads & Conversion Intelligence MCP Server

by raihan675

Prepare & Hash Custom Audience Payload

prepare_custom_audience_payload

Normalize emails to lowercase and trim, convert phone numbers to E.164, then hash them with SHA-256 for custom audience uploads. Optionally add or remove members automatically.

Instructions

Normalizes raw emails (trimmed, lowercase) and phone numbers (E.164 standard) into SHA-256 hashes per OpenAI specification. Optionally uploads the hashed members directly to a custom audience.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNoWhether to add or remove members if auto-uploadingadd
emailsNoList of plain-text customer emails to normalize and hash
phonesNoList of plain-text phone numbers (e.g., '+1 415-555-2671' or '4155552671')
auto_uploadNoIf true and custom_audience_id is set, immediately dispatch mutation
custom_audience_idNoOptional audience ID to automatically upload to

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior4/5

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

The description discloses meaningful behavioral details beyond basic operation: emails are trimmed and lowercased, phones are normalized to E.164, hashing uses SHA-256, and uploading is optional. With no annotations available, this is a strong attempt to describe side effects and transformations, though it does not cover all consequences such as removal behavior or return values.

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 two tightly written sentences with the core transformation front-loaded and the conditional side-effect clearly stated afterward. There is no filler or redundancy.

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?

The description provides the essential transformation and optional upload capability, which is adequate for a moderately complex tool. However, with no output schema and no annotations, it omits return behavior and explicit selection criteria relative to overlapping siblings, leaving some context for the agent to infer.

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 description coverage is 100%, so the baseline is 3. The description reinforces the normalization behavior and optional upload, but it adds little semantic meaning beyond what the input schema already documents for each parameter.

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 a specific operation: normalizing raw emails and phone numbers into SHA-256 hashes, with optional direct upload to a custom audience. This clearly identifies the tool's resource and action, though it doesn't explicitly differentiate itself from sibling tools like mutate_audience_membership.

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 guidance is provided about when to use this tool versus alternatives such as mutate_audience_membership or other custom-audience tools. The optional upload behavior creates overlap with mutation tools, but the description never says use this for raw PII or use mutate_audience_membership for already-hashed members.

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