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clerk.revoke_m2m_token

Revoke an M2M token by id in a connected Clerk instance.

Sensitive — invalidates a machine authentication token.

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

Returns the revoked M2M token.

Cost = 8 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
m2m_token_idYesClerk M2M token id (mt_...) to revoke.
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
m2m_tokenNoRevoked M2M token from the Backend API.

Schema Changelog

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

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are present, so the description carries the full burden. It explicitly warns 'Sensitive' and explains the consequence: 'invalidates a machine authentication token.' It also discloses the return value ('Returns the revoked M2M token') and default connection behavior, giving a clear behavioral picture.

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 compact and front-loaded: purpose, warning, usage flow, return, and cost are each covered in short sentences. There is no filler or redundant detail.

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?

For a destructive revoke tool with no annotations, the description covers purpose, side effects, usage flow, and return value. The output schema handles return format details. The only minor omission is explicit mention of irreversibility, but 'invalidates' already implies it.

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?

The input schema already describes both parameters with 100% coverage, including prefixes and default behavior. The description's parameter-related guidance ('Call clerk.get_connected_accounts first', 'Pass clerk_instance_id... or omit') largely restates schema content, adding only a sequential prerequisite.

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 opens with 'Revoke an M2M token by id in a connected Clerk instance,' using a specific verb and resource. The 'Sensitive' callout and 'invalidates a machine authentication token' further clarify the action, and the structure distinguishes it from other revoke_* siblings by targeting M2M tokens.

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?

It states 'Call clerk.get_connected_accounts first' and explains the two modes for targeting a connection ('Pass clerk_instance_id to target a specific connection, or omit it to use the default account'). This provides clear context on how to use the tool, though it doesn't explicitly describe exclusions or alternatives.

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.