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mh-zeynal

gapify-mcp-server

by mh-zeynal

Messages API: List all messages

gapify_client_list_messages
Read-onlyIdempotent

Retrieve the complete message history for a specific client conversation. Use this tool to list all messages exchanged between a contact and a designated inbox.

Instructions

List all messages in the conversation [Messages API] GET /public/api/v1/inboxes/{inbox_identifier}/contacts/{contact_identifier}/conversations/{conversation_id}/messages Auth: User API key (header api-access-token). 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
conversation_idYesThe numeric ID of the conversation
inbox_identifierYesThe identifier obtained from API inbox channel
contact_identifierYesThe source id of contact obtained on contact create

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive behavior, so the bar is lower, and the description adds two concrete traits beyond them: the required auth header (api-access-token) and the data-encoding caveat that text may arrive in Persian and digits may be Persian/Arabic-Indic. It omits return shape and pagination behavior, keeping it out of the top band.

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?

The core purpose is front-loaded in the first sentence, followed by the endpoint and auth, with the encoding caveat last. It is compact overall, though the Persian-digit sentence is somewhat tangential to listing messages.

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 list tool with no output schema, the description never indicates what is returned (message fields, ordering) or whether results are paginated/limited, which an agent needs before calling. Auth and encoding details are covered, but the return-side gap keeps this at minimum viable.

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%, so the schema already documents all three required identifiers and their meaning. The description adds only the endpoint template, which restates where each parameter belongs rather than adding new semantic detail, matching the baseline 3.

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 names a specific verb and resource ('List all messages in the conversation') and pins the resource with an explicit endpoint path showing the inbox/contact/conversation hierarchy. It does not, however, distinguish this client-facing tool from the platform sibling gapify_get_messages, so an agent can't route between them from the text alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied by the endpoint path and the 'User API key' auth note, which signals the public/client API scope. There is no explicit when-to-use, when-not-to-use, or reference to the sibling gapify_get_messages alternative.

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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