Skip to main content
Glama

clerk.list_organization_invitations

List organization invitations across a Clerk instance. Optionally filter to one organization via organization_id.

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

Returns invitation summaries and total_count.

Cost = 5 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (1–500).
offsetNoNumber of results to skip before returning.
statusNoFilter by invitation status: pending, accepted, revoked, or expired.
organization_idNoFilter invitations to a specific Clerk organization id (org_...).
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
invitationsNoInvitations returned for the requested page.
total_countNoTotal number of invitations matching the filter.

Schema Changelog

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

  1. Changed5 schema fields changed
    • addedInput schema / properties / organization_id / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • addedInput schema / properties / organization_id / default
      Added value: +null
    • changedInput schema / properties / organization_id / description
      Previous value: -"Clerk organization id (org_...) to operate on."New value: +"Filter invitations to a specific Clerk organization id (org_...)."
    • removedInput schema / properties / organization_id / type
      Removed value: -"string"
    • removedInput schema / required
      Removed value: -[
      -  "organization_id"
      -]
  2. Added

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds context beyond the schema by specifying the prerequisite call, default account behavior, return shape ('invitation summaries and total_count'), and a cost of 5 tokens. It does not detail pagination behavior or deeper side effects, but the read-only nature of 'List' plus the return info is reasonably transparent.

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 extremely concise: three short paragraphs front-load the purpose, then provide usage guidance, then state return and cost. Every sentence conveys useful information without redundancy or filler.

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?

Given the tool has an output schema and a fully documented input schema, the description supplies the missing contextual pieces: why to call get_connected_accounts first, how to choose an instance, optional filtering, return summary, and cost. Nothing essential is left unexplained for a list operation with this schema richness.

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 the baseline is 3. The description adds meaning beyond the schema for organization_id ('Optionally filter to one organization') and clerk_instance_id ('Call clerk.get_connected_accounts first... omit to use the default account'), which are the two most context-heavy parameters. This raises the score above baseline.

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 uses a specific verb ('List') and resource ('organization invitations'), and clearly scopes the operation 'across a Clerk instance.' It also mentions the optional organization_id filter, which distinguishes this from cluster-wide or user-invitation listing tools like clerk.list_invitations.

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 provides a clear prerequisite ('Call clerk.get_connected_accounts first') and explains how to use clerk_instance_id to target a connection or default to the account. It lacks explicit exclusionary guidance (e.g., 'use list_invitations for user invitations'), but the context is clear enough for selecting this tool.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.