gapify-mcp-server

Contacts: Contact Conversations

gapify_list_contact_conversations

Read-onlyIdempotent

Retrieve all conversations for a specific contact using account and contact IDs, so support agents can review prior interactions and context.

Instructions

List the conversations of a contact [Contacts] GET /api/v1/accounts/{account_id}/contacts/{id}/conversations 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.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "account_id": "<account_id>",
      "id": "<id>"
    },
    "name": "gapify_list_contact_conversations"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	ID of the contact
`account_id`	Yes	The numeric ID of the account

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Oct 20, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description usefully adds the auth requirement (User API key in an `api-access-token` header) and a note that text and digits may arrive in Persian/Arabic-Indic form, which is real input-handling context. It says nothing about pagination or result volume, which is the main remaining gap.

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 purpose is front-loaded in the first clause, and the endpoint, auth header, and localization caveat are attached compactly. The Persian/Arabic-Indic digits sentence is somewhat tangential to listing conversations but does inform how callers should format values, so it earns most of its space.

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?

With no output schema, the description carries the burden of explaining what comes back, yet it never describes the response shape or whether results are paginated. Auth, scope, and input encoding are covered, so it is adequate but leaves a noticeable gap for a list endpoint.

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% for both parameters, so the schema fully documents `id` and `account_id`; that establishes a baseline of 3. The description adds no further meaning about these parameters, such as format expectations for the contact ID.

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 with a scope qualifier: 'List the conversations of a contact'. This is clearly distinguishable from the broader gapify_list_conversations sibling because the scope is narrowed to a single contact, though the description never names that sibling to make the contrast explicit.

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 and no routing to alternatives. The tool sits alongside gapify_list_conversations, gapify_filter_conversations and gapify_get_conversation, and the description offers nothing to help an agent choose between them beyond the implied contact scoping.

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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