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Vee3

by io.github.Vee3io

clerk.create_sign_in_token

Create a sign-in token for a user in a connected Clerk application. The token can be used once to sign the user in without credentials (magic-link style).

Sensitive — the returned token is a high-privilege secret that grants sign-in access; do not log or expose it.

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

Cost = 15 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idYesClerk user id (user_...) to retrieve or modify.
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.
expires_in_secondsNoToken lifetime in seconds (minimum 1). Defaults to 2592000 (30 days).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sign_in_tokenNoCreated Clerk sign-in token object from the Backend API.

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 provided, the description carries the full burden and does well: it calls out the token as a high-privilege secret, one-time use, and warns against logging or exposing it. This is valuable behavioral context beyond the schema, though it omits potential auth prerequisites or side effects.

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 short, purposeful sentences: purpose, sensitivity warning, usage instruction, and cost. The description is front-loaded with the core action and contains no redundant or filler content.

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?

Description covers purpose, sensitivity, prerequisite, and connection selection. Combined with the complete schema and output schema, it gives enough context to invoke correctly. Missing error cases or permission requirements, but these are not critical for a token-creation action.

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 coverage is 100%, so baseline is 3. The description repeats the clerk_instance_id usage from the schema ('omit to use the default') and adds the get_connected_accounts prerequisite, but provides no new parameter-level meaning beyond the schema's own descriptions.

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?

Description states a specific verb ('Create a sign-in token') and resource ('user in a connected Clerk application'), further clarifying that the token enables credential-free sign-in (magic-link style) and is one-time use. This clearly distinguishes it from sibling tools like create_session_token or create_actor_token.

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?

Description gives an explicit prerequisite ('Call clerk.get_connected_accounts first') and precise instructions for targeting a connection (pass clerk_instance_id or omit for default). It does not explicitly cite alternatives or exclusions, but the context strongly implies when this tool is appropriate.

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.

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