Invite a person by email to collaborate on this project. Returns the new invitation record; the invitee receives an email with an accept link. Enforces the seat cap for the plan tier. Owner only.
| Name | Required | Description | Default |
|---|---|---|---|
| role | Yes | Role to assign on acceptance. | |
| Yes | Email address to invite. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only indicate non-read-only and non-destructive. The description adds meaningful behavior: the returned invitation record, the email with accept link, seat cap enforcement, and owner-only restriction. This is substantial context beyond the annotations, though it doesn't cover error cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: first states purpose, second describes return and side effect, third lists constraints. Every sentence adds value with no repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description correctly explains the return value ('Returns the new invitation record') and covers side effects and constraints. It could mention duplicate emails or seat cap errors, but these are not critical for a typical use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both role and email. The description does not add any extra meaning to the parameters beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Invite a person by email'), the resource ('this project'), and the outcome ('collaborate'). This distinguishes it from sibling tools like remove_member, resend_invite, and set_member_role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides key context by noting 'Owner only' and 'Enforces the seat cap', which implies when it should or shouldn't be used. However, it doesn't explicitly name alternative tools for related actions (e.g., resend_invite), so it's not a perfect 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources and the descriptions are unusually explicit, but the billing cluster (change_plan/cancel_subscription and the many add-on actions) plus the preview/diff tools overlap and could cause mis-selection. config_diff, dry_run_endpoint, and preview_line_draft all read as 'preview what will change' at first glance despite different scopes.
The overwhelming majority follow a clean snake_case verb_noun pattern: create_*, get_*, list_*, set_*, update_*, delete_*. It is only held back by a few naming outliers such as config_diff and default_endpoint_template, which break the verb-first convention.
78 tools is an extreme mismatch for an MCP server surface, even accounting for the broad management/relay domain. Such a large surface will overwhelm model context and make tool selection materially harder; this would be better split into focused servers for configuration, data-plane operations, and billing.
The tool surface is very thorough: projects, lines, endpoints, credentials, keys, configs/drafts, DLQ, requests, metrics, audit, team, and billing are all represented. Only minor gaps exist, such as no direct single-line get/update and the intentional inability to widen the outbound allowlist or lift archive protection via API.
