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Zendesk MCP Server by Fruggr

List Promoted Help Center Articles

list_promoted_articles
Read-onlyIdempotent

Lists promoted Help Center articles by scanning article pages because Zendesk has no server-side promoted filter; returns metadata only for the default locale.

Instructions

List the promoted ("featured") Help Center articles — the small, editorially-curated set surfaced at the top of their sections. Returns metadata only (no body); use get_article for full content. COST: the Help Center API has no server-side promoted filter, so this scans article pages (one Zendesk API request per page, up to ARTICLE_RESOURCES_SCAN_MAX_PAGES, default 20) and filters client-side — potentially costly on a large Help Center. Each call performs a fresh, uncached scan, so avoid calling it repeatedly. On a very large Help Center some promoted articles may be omitted, and both the omission and the number of pages scanned are flagged in the output. Lists the default locale. To promote or unpromote an article, use update_article with promoted (requires Help Center admin / Guide admin rights).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.24.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv2.16.1

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower, yet the description adds substantial non-obvious behavior: no server-side promoted filter, client-side filtering over up to ARTICLE_RESOURCES_SCAN_MAX_PAGES (default 20) API requests, no caching, and possible omission of promoted articles on very large Help Centers that is flagged in the output.

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-loaded with the purpose and the get_article/update_article routing, then the cost model. It is dense and slightly long, but nearly every clause carries operational value; only minor tightening is possible.

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

Completeness5/5

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

No output schema exists, and the description compensates by stating what is returned (metadata only, no body), that the default locale is used, and that truncation and page counts are surfaced in the output. Nothing an agent needs to decide whether to call it is missing.

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?

There are zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. It does usefully clarify the implicit scoping behavior — that it lists the default locale — which an agent could otherwise assume was configurable.

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 the promoted ("featured") Help Center articles') and narrows the scope precisely ('the small, editorially-curated set surfaced at the top of their sections'). It explicitly differentiates from siblings: 'use get_article for full content' and 'use update_article with `promoted`' to mutate.

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

Usage Guidelines5/5

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

Gives explicit when-to-use (reading the curated featured set), when-not-to-use (full content belongs to get_article), the mutation alternative (update_article, with the admin-rights prerequisite), and a strong operational caveat to avoid repeated calls. Nothing is left to inference.

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