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gmail-mcp

gmail-mcp

by DimitrisPasakaleris
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

mark_emails_read

Marks multiple Gmail messages as read in one request using batch operations, avoiding individual calls for each email.

Instructions

CHOICE HINT: When the user asks to "mark as read" or "mark read" multiple
emails, ALWAYS prefer this tool over making N calls to mark_read(). It uses
Gmail's batchModify API in chunks of at most 1000 message IDs.

Mark multiple emails as read in a single MCP request.

Uses messages().batchModify() with up to 1000 IDs per Gmail API call.

Required:
  message_ids (list[str]) — Gmail message IDs.

Returns on success:
  {"ok": true, "data": {
    "requested": N, "succeeded": N, "failed": 0,
    "results": [{"id": "...", "ok": true}, ...]
  }}

Workflow note: Use this instead of N calls to mark_read() to bundle
  all operations into a single MCP request.

Input Schema

NameRequiredDescriptionDefault
message_idsYes

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 full burden and does so well: it names the underlying Gmail batchModify API, discloses the 1000-ID chunking limit, and gives the exact success payload including per-ID ok flags and a failed count, which signals partial-failure tolerance. It stops short of describing auth/scope requirements or what happens with invalid or missing IDs, so it falls just shy of a 5.

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

Conciseness3/5

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

The CHOICE HINT is correctly front-loaded, but the content is then restated twice — the batchModify API and the "use this instead of N calls to mark_read()" rule each appear in two places. Trimming the duplicated workflow note would lose no information.

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?

For a single-parameter batch tool with no annotations and no output schema, the description supplies the routing rule, the batching mechanism, the chunk limit, and the concrete return shape. Nothing essential to calling it correctly 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%, so the description must compensate; it names the parameter, its type (list[str]), and clarifies the values are Gmail message IDs. The 1000-per-chunk constraint also implicitly bounds the list, adding meaning absent from the bare array schema.

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 ("Mark multiple emails as read") and explicitly distinguishes from the single-item sibling mark_read by preferring this tool for multi-email requests. An agent can select between the two without opening either schema.

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?

The CHOICE HINT states the trigger condition ("when the user asks to 'mark as read' ... multiple emails") and the exact alternative to avoid (N calls to mark_read()). The workflow note reinforces the same routing rule, leaving nothing to inference.

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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