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mh-zeynal

gapify-mcp-server

by mh-zeynal

Contacts API: Create a contact

gapify_client_create_contact

Create a contact in a Gapify inbox through the Contacts API to add customer details such as identifier, email, name, phone, avatar, and custom attributes.

Instructions

Create a contact [Contacts API] POST /public/api/v1/inboxes/{inbox_identifier}/contacts Body fields: identifier, identifier_hash, email, name, phone_number, avatar_url, custom_attributes. Extra fields can be passed via extra_body. Text values may be written in Persian (Farsi) or any other language and are sent unchanged; IDs, numbers and phone numbers may use Persian or Arabic-Indic digits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoName of the contact
emailNoEmail of the contact Example: "user@example.com"
avatar_urlNoThe url to a jpeg, png file for the user avatar Example: "https://example.com"
extra_bodyNoAdditional JSON body fields to merge into the request (for keys not listed above).
identifierNoExternal identifier of the contact
phone_numberNoPhone number of the contact
identifier_hashNoIdentifier hash prepared for HMAC authentication
inbox_identifierYesThe identifier obtained from API inbox channel
custom_attributesNoCustom attributes of the customer Example: {}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true), so the bar is lower. The description adds real behavioral context beyond that: the extra_body merge escape hatch, and that text is sent unchanged in any language while Persian/Arabic-Indic digits are accepted in IDs and phone numbers. It still omits error/duplicate behavior and auth requirements for identifier_hash.

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

Conciseness3/5

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

Front-loaded with the verb and endpoint, which is good, but the enumeration of body fields duplicates the schema almost verbatim and consumes most of the description without adding meaning. The language/digit sentence is the only part that clearly earns its place.

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 create-mutation with no output schema, the description covers the endpoint and inputs but says nothing about the response (created contact payload), error conditions such as duplicate identifiers, or required permissions. Annotations cover the safety profile, so the gap is moderate rather than severe.

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 schema already documents each field and the baseline is 3. The description largely re-lists the same fields, though the note about Persian/Arabic-Indic digits in IDs, numbers and phone numbers adds genuine input-format semantics the schema does not carry.

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?

States a specific verb and resource ('Create a contact') and pins it to a concrete endpoint (POST /public/api/v1/inboxes/{inbox_identifier}/contacts), so the agent knows exactly what happens. It does not distinguish itself from the sibling gapify_create_contact or gapify_client_create_contact, leaving the agent to infer which API surface applies.

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?

There is no when-to-use guidance, no statement of prerequisites, and no mention of the near-identical siblings gapify_create_contact / gapify_client_get_contact / gapify_client_update_contact. The agent must guess whether this is the public-API variant or the conversational-client variant.

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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