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gapify-mcp-server

gapify-mcp-server

by mh-zeynal
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Canned Responses: List all Canned Responses in an Account

gapify_list_canned_responses
Read-onlyIdempotent

List all saved reply templates (canned responses) for a Gapify account by account ID, so support agents can review and reuse approved replies.

Instructions

List all canned responses (saved reply templates) in the account [Canned Responses] GET /api/v1/accounts/{account_id}/canned_responses 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>"
    },
    "name": "gapify_list_canned_responses"
  }
}

Input Schema

NameRequiredDescriptionDefault
account_idYesThe numeric ID of the account

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds value beyond them by disclosing the auth requirement (User API key in the api-access-token header), the exact endpoint, and language/digit handling notes for returned text.

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?

Front-loads the core purpose, then the endpoint, auth, and language note. It is compact and each line earns its place, though the Persian/Arabic-Indic digit note is somewhat tangential to a list operation.

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

Completeness4/5

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

For a single-parameter read tool with annotations covering safety and no output schema, the description covers auth and endpoint details adequately. No major gaps remain for correct invocation.

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 the single account_id parameter, so the schema already documents it. The description adds no parameter-level detail (e.g., format expectations), matching the baseline 3 when the schema does the heavy lifting.

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?

States a specific verb and resource: 'List all canned responses (saved reply templates) in the account'. The parenthetical clarifies the domain term, and the operation is clearly distinguishable from sibling mutations like gapify_add_canned_response and gapify_update_canned_response.

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?

No explicit when-to-use or when-not-to-use guidance is given. For a simple read/list tool the usage is largely implied by the name, but the description offers no routing cues relative to alternatives such as filtering or searching canned responses.

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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