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clerk.list_users

List users in a connected Clerk application.

Call clerk.get_connected_accounts first. Pass clerk_instance_id to target a specific connection, or omit it to use the default account.

Returns user id, name, primary email, and created_at for each user, plus total_count.

Cost = 5 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of users to return (1–500).
offsetNoNumber of users to skip before returning results.
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
usersNoUsers returned for the requested page.
total_countNoTotal number of users in the Clerk application.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the prerequisite connection, the exact return fields (including total_count), and the token cost. It does not mention pagination or sorting, but for a read-only listing tool this is acceptable, especially since the return shape is described.

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?

The description is four sentences, front-loaded with the core purpose, and every sentence adds meaningful context: prerequisite, parameter choice, return payload, and cost. 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?

Given the tool's simplicity, the description is quite complete: it explains the connection prerequisite, default behavior, returned fields, and cost. The output schema exists, so return values need no further elaboration. Lacks discussion of pagination edge cases, but that is not a significant gap for this tool.

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?

Schema coverage is 100%, so parameters are well-documented by the schema. The description adds value by explaining the behavior of clerk_instance_id (target a specific connection or omit for default), which goes beyond the schema's 'omit to use default' note. It does not elaborate on limit/offset, but those are self-explanatory.

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 specific action 'List users' with a clear resource ('connected Clerk application') and explicitly notes it returns user id, name, primary email, and created_at. It distinguishes itself from sibling list_* tools by specifying the resource type (users) and providing connection context.

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?

The description explicitly instructs to call clerk.get_connected_accounts first and explains how to target a connection via clerk_instance_id, which is a clear usage prerequisite. It does not discuss when to choose this over alternatives like clerk.count_users, but it provides enough context to know when to use this tool for listing users.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a distinct purpose, further clarified by group prefixes and clear descriptions. Within each group, tools perform different operations (e.g., domains.lookup vs. domains.whois vs. domains.rdap) with no ambiguity.

Naming Consistency5/5

All tools follow a consistent group.tool_name pattern using snake_case. The naming is predictable and uniformly applied across all groups.

Tool Count4/5

78 tools is high, but the server aggregates multiple distinct API domains (11 groups). Each group has a reasonable number of tools, typically under 10, with TikTok having 17. The count reflects breadth, not bloat.

Completeness5/5

Each domain's tool set covers the primary expected operations (e.g., search, details, reviews, metrics, user info). There are no obvious gaps for read-only analytical use; features like posting are likely out of scope.