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Parabol MCP by usefulapi

Invite users to a team

invite_to_team
Destructive

MUTATES Parabol data: send team invitations by email. Required: teamId and invitees (an array of email addresses). Optionally scope to a meetingId. Parabol GraphQL: inviteToTeam(teamId, invitees). Requires TEAMS_WRITE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamIdYesThe team id to invite into (required).
inviteesYesEmail addresses to invite (required).
meetingIdNoOptionally associate the invitation with a meeting id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only supply destructiveHint=true, so the description carries most of the behavioral load and does so well: it declares the mutation nature, the authorization requirement (TEAMS_WRITE), and the outward-facing side effect that emails are actually sent. It stops short of covering failure/duplicate-invite behavior or rate limits.

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?

Three compact sentences, mutation warning front-loaded, followed by requirements and permission. Every clause carries information and nothing is padded.

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?

For a 3-parameter mutation with no output schema, the description covers purpose, required inputs, scoping, and the permission gate. Only return/error semantics and duplicate-invite behavior are unaddressed, which is a minor gap.

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 all three parameters are already documented in the schema. The description only restates which are required and which is optional, adding no format, validation, or edge-case detail beyond the schema — the baseline 3 for full coverage.

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 names a specific verb and resource ('send team invitations by email') and explicitly flags it as a mutation of Parabol data. It also gives the underlying GraphQL mutation signature, so an agent can distinguish it immediately from read-oriented siblings like list_team_members or get_team.

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 the required parameters, the optional meetingId scoping, and the required TEAMS_WRITE permission, which is clear usage context. It does not name an alternative tool or a when-not-to-use condition, but no sibling competes for this operation.

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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