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Glama

YouSpot

Read email

get_gmail_message
Read-only

Fetch one Gmail message by its id from the user's connected mailbox, including the full plain-text body (rare header-only connections get headers and the snippet instead). Use this to read a message found via search_gmail_messages (which returns ids and snippets only), or when a triggering event hands you a Gmail message_id to analyze.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNoEmail address of the connected mailbox holding the message. Omit to try all connected mailboxes.
message_idYesThe Gmail message id.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

The readOnlyHint annotation already marks this as a safe read operation, and the description adds meaningful behavioral details: the response includes the full plain-text body, with a documented edge case for header-only connections. This goes beyond the annotation and gives the agent realistic expectations for output content.

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?

Two concise, information-dense sentences. Key purpose and usage come first, and the behavioral exception is placed naturally without bloat. Every clause earns its place.

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?

Given a simple two-parameter schema, full schema coverage, a read-only safety annotation, and no output schema, the description provides enough context: what it fetches, what the body looks like, the rare header-only case, and when to use it. An agent should be able to invoke this tool correctly with no additional guidance.

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 fully documents both parameters. The description reinforces the role of message_id but does not add detail beyond the schema. Baseline 3 is appropriate because the description does not need to compensate for missing schema information.

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?

The description states a specific verb and resource: 'Fetch one Gmail message by its id' from the connected mailbox. It also clarifies what the tool returns (full plain-text body, or headers/snippet for rare header-only connections), distinguishing it from sibling search_gmail_messages which returns only ids and snippets.

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 description explicitly names the intended use cases: reading a message found via search_gmail_messages, or analyzing a message_id from a triggering event. It also contrasts with search_gmail_messages by noting that search returns ids and snippets only, so an agent knows when to switch to this tool.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools are scoped to a distinct resource and action, and descriptions do a good job separating close pairs like search_connections vs ask_about_connections or get_my_linkedin_posts vs linkedin_analytics. However, the multiple deletion tools (delete_graph_object, delete_graph_objects, purge_graph_object) and the several file-reading tools are easy to confuse without reading the descriptions carefully.

Naming Consistency4/5

The vast majority of tools follow a clear verb_noun pattern such as create_, get_, list_, search_, send_, and delete_. A handful of noun-phrase outliers like linkedin_analytics, mutual_connections, top_message_correspondents, and what_needs_attention break the pattern, so it is highly consistent but not perfect.

Tool Count1/5

64 tools is an extreme count, far beyond the typical well-scoped 3-15 tool range and even beyond the 25+ threshold for 'too many'. While the server covers many integrations, this many tools creates a heavy navigation burden and would be better split into focused servers per domain.

Completeness3/5

Core graph/CRM operations and read-side integration coverage are strong, with search, get, list, and create tools across most domains. However, there are notable dead ends: no delete_calendar_event, no tracker management beyond create_tracker, and set_follow_up explicitly lacks a read-back query tool, so some natural user requests cannot be completed through the toolset.