drop2run-mcp

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by Drop-to-run

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TypeScript

Local

Invite people to a site

invite_people

Idempotent

Add email addresses to a site's list and send each person an invitation from the account; choose view or comment access. One bad address or an over-limit list adds nobody.

Instructions

Adds email addresses to a site's list and emails each new one an invitation from the account. Use only addresses the person gave you — never guess, infer or look one up. comment lets them comment as well as open it. Inviting does not make the site private; update_site's invitedOnly: true does. On plans with private sharing; all or nothing — one bad address, or a list past the plan's limit, adds nobody.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "site": "<site>",
      "emails": "<emails>"
    },
    "name": "invite_people"
  }
}

Input Schema

Name	Required	Description
`role`	No	`view` (the default) to open the site, `comment` to open it and comment.
`site`	Yes	Subdomain or site id, from list_sites.
`emails`	Yes	The addresses, exactly as the person gave them.

Output Schema

Name	Required	Description
`added`	Yes	Addresses added and emailed.
`total`	Yes	How many are on the list now.
`alreadyListed`	Yes	Addresses already on the list, left as they were and not emailed again.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.5Oct 14, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Goes well beyond the annotations: emails are sent from the account, the operation is all-or-nothing (one bad address or over-limit list adds nobody), it requires a plan with private sharing, and it does not itself make the site private. This is rich behavioral context annotations do not carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, then dense but purposeful clauses. Every sentence carries information, though the multi-clause structure is slightly compressed.

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?

With an output schema present and annotations covering safety/idempotency, the description fills the remaining gaps: prerequisites (private-sharing plan), atomicity, and the privacy distinction. Nothing an agent needs is missing.

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 the schema already documents `role`, `site`, and `emails`. The description restates the `comment` effect and email sourcing, adding marginal value over structured fields. Baseline 3 applies.

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?

States a specific verb and resource: adds email addresses to a site's list and sends invitations. Clearly distinguishable from siblings like remove_person, list_people, and update_site.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly constrains input ('use only addresses the person gave you — never guess, infer or look one up') and routes the privacy decision to the alternative: 'Inviting does not make the site private; update_site's `invitedOnly: true` does.'

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