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NikolayChernuhaN2W

Zendesk MCP Server

export_tickets

Export Zendesk tickets matching a search query to a JSON Lines file for analysis. Supports resuming large exports across multiple calls.

Instructions

Export every ticket matching a Zendesk search to a JSON Lines file in the export folder, one ticket per line, for analyzing more tickets than fit in a conversation. Large exports take several calls: while done is false, call again with only the returned resume value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoZendesk search query, e.g. 'created>2026-01-01 tags:backup'. Required unless resuming
resumeNoThe resume value from the previous call, to continue an export
file_nameNoFile name inside the export folder (default tickets-<timestamp>.jsonl)
include_commentsNoAlso export each ticket's full conversation (one extra request per ticket, so much slower)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/destructive hints. The description adds valuable non-annotation behavior: large exports require multiple calls, continuation depends on a returned resume value, and output is written to the export folder. It does not fully describe the response shape, but adds meaningful stateful behavior context.

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?

Two focused sentences: the first front-loads purpose, output format, and rationale; the second explains the pagination/resume behavior. There is no filler or redundancy.

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 tool with no output schema and no required parameters, the description covers the core aspects: what is exported, where it is written, the file format, and the resumable multi-call behavior. It could be more explicit about the exact return fields, but the description gives enough for an agent to call and continue the export correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers all four parameters at 100%, so the baseline is 3. The description adds extra value by explaining the resume continuation pattern ('call again with only the returned resume value'), which sharpens how the resume parameter is meant to be used beyond the schema description.

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?

The description states a precise verb + resource ('Export every ticket matching a Zendesk search to a JSON Lines file'), adds file format details ('one ticket per line'), and gives a clear use case ('for analyzing more tickets than fit in a conversation'). This distinguishes it from sibling search/list/get tools despite not naming them.

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

Usage Guidelines4/5

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

It clearly says when to use this tool: when you need to analyze more tickets than fit in a conversation, and it explains the multi-call resume pattern. It does not explicitly name alternatives or state when not to use it, so it stops short of a full 5.

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