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clerk.list_api_keys

List API keys 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 api_keys and total_count.

Cost = 5 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of API keys to return (1–500).
queryNoSearch query to filter API keys by name.
offsetNoNumber of API keys to skip before returning results.
subjectYesSubject to list API keys for (user_... or org_...).
key_typeNoFilter by API key type (typically "api_key").
include_invalidNoWhen true, include revoked or expired API keys.
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keysNoAPI keys matching the request.
total_countNoTotal number of API keys matching the filters.

Schema Changelog

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

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses a prerequisite (get_connected_accounts), the instance selection behavior, returns, and cost. The read-only nature is implicit via 'list.' The cost and prerequisite add useful context beyond the schema.

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 short sentences with no redundant content. It front-loads the core purpose, then provides necessary contextual steps, return info, and cost—all without waste.

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?

The description covers prerequisite, instance targeting, return fields, and cost. Output schema exists, so return details are not needed. Minor gaps like pagination behavior are covered by schema params. Overall, sufficiently complete for a list tool.

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%, so the schema already documents all parameters. The only extra note is 'Pass clerk_instance_id... or omit,' but the schema already includes that detail. No significant additional meaning is added beyond the schema.

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 'List API keys in a connected Clerk application,' providing a specific verb, resource, and scope. This clearly distinguishes it from related tools like clerk.get_api_key (single key) and clerk.create_api_key (creation).

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 gives clear context: 'Call clerk.get_connected_accounts first' and explains how to target a specific instance or use the default. It lacks explicit exclusions or named alternatives, but the context is solid.

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.