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gws-mcp

gws-mcp

by samuel-stidham
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

gmail_modify

Add or remove labels on Gmail messages and threads to control archive, read state, star, and trash.

Instructions

Add or remove labels by name on messages or threads; covers archive, read state, star, trash.

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": {
      "account": "<account>"
    },
    "name": "gmail_modify"
  }
}

Input Schema

NameRequiredDescriptionDefault
accountYes
add_labelsNo
thread_idsNo
message_idsNo
remove_labelsNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description must disclose all behavioral traits. It mentions that the tool 'covers' special states like archive, read state, star, and trash, which are implemented as labels, but does not detail permissions, rate limits, error behavior, or what happens if labels are missing. Some transparency is present, but significant gaps remain.

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?

The description is a single sentence of 15 words, which is very concise. However, it sacrifices detail that could be provided in a slightly longer, structured format. It earns its place but leaves out parameter information that would improve usability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has a moderate number of parameters (5) and an output schema (not shown but present). The description does not explain the relationship between thread_ids and message_ids, the behavior when both are provided, or the necessity of the account parameter. While the output schema can handle return values, the description's gaps in parameter semantics and usage reduce completeness for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage (only titles, no descriptions). The tool description does not elaborate on any parameter beyond the phrase 'by name', which hints at label names but does not explain the format of add_labels and remove_labels, the distinction between thread_ids and message_ids, or the requirement of the account parameter. The description adds minimal semantic value beyond the schema titles.

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?

Description clearly states the verb ('Add or remove labels') and the resource ('messages or threads'). It also enumerates covered actions (archive, read state, star, trash), which differentiates it from sibling tools like gmail_search, gmail_read, and gmail_send.

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

Usage Guidelines3/5

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

The description implies that the tool is for label modification, but it does not explicitly state when to use it versus alternatives, nor does it provide when-not or exclusion criteria. The usage context is only implied, offering no explicit guidance.

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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