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gmail-mcp

gmail-mcp

by DimitrisPasakaleris
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_drafts

Retrieve draft emails from Gmail's Drafts folder, optionally limiting results, to review subjects, recipients, and draft IDs before editing or deleting them.

Instructions

List the user's draft emails from Gmail's Drafts folder.

Optional:
  max_results (int, default=5) — max drafts to return.

Returns on success:
  {"total": N, "drafts": [
    {"id": "...", "subject": "...", "from": "...", "to": "...",
     "date": "...", "snippet": "..."}
  ]}

Workflow note: Each draft has a "id" (draft_id) used by update_draft
  and delete_draft. The "subject" field shows the draft's subject line.
  Use update_draft(draft_id, body="new content") to edit a draft.

Input Schema

NameRequiredDescriptionDefault
max_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the default (5), the return payload shape, that each item carries an id usable by update_draft/delete_draft, and that body content is represented only by a snippet. It omits ordering/sort behavior and any permission or rate-limit notes.

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?

Front-loaded one-line purpose, then clearly labeled Optional / Returns / Workflow blocks. Every block carries information the agent needs and there is no 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?

There is no output schema and no annotations, so the description must cover returns and safety context; it supplies the exact response shape and the id-to-downstream-tool relationship. For a one-parameter read tool, nothing essential is missing.

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 0%, and the description fully compensates for the single parameter by restating its type, default, and meaning ("max drafts to return"). Nothing more is needed for one optional integer, though it adds no nuance about upper bounds or pagination beyond that.

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 ("List the user's draft emails") plus the source scope ("Gmail's Drafts folder"). The word "draft" inherently separates it from the sibling list_emails/read_email tools, and the workflow note naming update_draft/delete_draft further pins its role.

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 "Workflow note" gives clear context for what to do with the results (update_draft, delete_draft) and how the id field is consumed. It stops short of explicit when-not guidance or naming list_emails as the alternative for non-draft messages, so it is clear but not fully routing.

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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