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Zendesk MCP Server by Fruggr

Zendesk MCP Server by Fruggr

List Request Forms

list_request_forms
Read-onlyIdempotent

Lists active customer-facing Zendesk Help Center request forms, returning each form's name, ID, and default status so users can choose the right request type before submitting.

Instructions

List the kinds of request you can submit to this Zendesk — the forms a customer picks between on the Help Center, such as "Report a bug" or "Feature request". Returns each form's customer-facing name, its numeric id, and which one is the account default. Call this first when opening a request so the user chooses the right kind, then get_request_form to learn what that form asks for. Only forms that are active and visible to end users are listed; an account with a single form returns just that one. This is the end-user view: agents picking a form for someone else want list_ticket_fields and create_ticket instead.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.9.1

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds real context beyond them: only active end-user-visible forms are returned, and a single-form account yields just one result. It also pre-announces the returned fields (name, id, default flag), which the absent output schema would otherwise leave unknown. The only gap is that it does not discuss pagination or result-size behavior if the hint of multi-form accounts scales.

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?

Four sentences, front-loaded with the identity of the resource, then the sequencing rule, then the scoping caveat, then the sibling exclusion. No redundant restatement of the title and no wasted clauses.

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 zero-parameter read tool with no output schema, the description covers purpose, sequencing, filtering semantics, and return shape, which is enough to call it correctly. Only result-volume or pagination behavior is unstated, a minor omission for a typically small list.

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 and 100% schema coverage, so the schema carries the full burden and the description correctly stays silent on inputs. Baseline applies; nothing further is needed.

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 kinds of request you can submit") and immediately concretizes it with the Help Center form examples "Report a bug" / "Feature request". It also names the two siblings it is not (list_ticket_fields, create_ticket), so an agent can route without opening another schema.

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 an explicit ordering rule ("Call this first when opening a request ... then get_request_form") and an explicit exclusion with the alternative for the agent/assist use case. Both when-to-use and when-not-to-use are covered.

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