Skip to main content
Glama
c0webster

Hardened Google Workspace MCP

by c0webster

draft_gmail_message

Create draft emails in Gmail for new messages or replies, supporting plain text or HTML formatting with CC/BCC options.

Instructions

Creates a draft email in the user's Gmail account. Supports both new drafts and reply drafts.

Args: user_google_email (str): The user's Google email address. Required. subject (str): Email subject. body (str): Email body (plain text). body_format (Literal['plain', 'html']): Email body format. Defaults to 'plain'. to (Optional[str]): Optional recipient email address. Can be left empty for drafts. cc (Optional[str]): Optional CC email address. bcc (Optional[str]): Optional BCC email address. thread_id (Optional[str]): Optional Gmail thread ID to reply within. When provided, creates a reply draft. in_reply_to (Optional[str]): Optional Message-ID of the message being replied to. Used for proper threading. references (Optional[str]): Optional chain of Message-IDs for proper threading. Should include all previous Message-IDs.

Returns: str: Confirmation message with the created draft's ID.

Examples: # Create a new draft draft_gmail_message(subject="Hello", body="Hi there!", to="user@example.com")

# Create a plaintext draft with CC and BCC
draft_gmail_message(
    subject="Project Update",
    body="Here's the latest update...",
    to="user@example.com",
    cc="manager@example.com",
    bcc="archive@example.com"
)

# Create a HTML draft with CC and BCC
draft_gmail_message(
    subject="Project Update",
    body="<strong>Hi there!</strong>",
    body_format="html",
    to="user@example.com",
    cc="manager@example.com",
    bcc="archive@example.com"
)

# Create a reply draft in plaintext
draft_gmail_message(
    subject="Re: Meeting tomorrow",
    body="Thanks for the update!",
    to="user@example.com",
    thread_id="thread_123",
    in_reply_to="<message123@gmail.com>",
    references="<original@gmail.com> <message123@gmail.com>"
)

# Create a reply draft in HTML
draft_gmail_message(
    subject="Re: Meeting tomorrow",
    body="<strong>Thanks for the update!</strong>",
    body_format="html,
    to="user@example.com",
    thread_id="thread_123",
    in_reply_to="<message123@gmail.com>",
    references="<original@gmail.com> <message123@gmail.com>"
)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_google_emailYes
subjectYesEmail subject.
bodyYesEmail body (plain text).
body_formatNoEmail body format. Use 'plain' for plaintext or 'html' for HTML content.plain
toNoOptional recipient email address.
ccNoOptional CC email address.
bccNoOptional BCC email address.
thread_idNoOptional Gmail thread ID to reply within.
in_reply_toNoOptional Message-ID of the message being replied to.
referencesNoOptional chain of Message-IDs for proper threading.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool creates drafts (implying a write operation) and mentions the return value ('Confirmation message with the created draft's ID'), adding some behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether drafts are saved automatically, leaving gaps for a mutation tool.

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 well-structured with a clear opening sentence, an 'Args' section listing parameters, a 'Returns' statement, and multiple examples. It is appropriately sized for a 10-parameter tool, but the extensive examples (5 cases) might be slightly verbose, though they earn their place by illustrating usage scenarios effectively.

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

Completeness4/5

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

Given the complexity (10 parameters, mutation tool) and no annotations, the description is fairly complete: it explains purpose, parameters, return value, and provides examples. However, it lacks details on authentication needs, error cases, or draft lifecycle (e.g., auto-save behavior), which would enhance completeness for a Gmail integration tool.

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 description coverage is high (90%), so the baseline is 3. The description adds value by explaining parameter roles beyond the schema: it clarifies that 'to' can be 'left empty for drafts', distinguishes 'thread_id' for 'reply drafts', and notes that 'in_reply_to' and 'references' are for 'proper threading'. This enhances understanding without repeating schema details.

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 clearly states the tool 'creates a draft email in the user's Gmail account' with specific verbs ('creates', 'draft') and resource ('Gmail account'), distinguishing it from sibling tools like 'get_gmail_message_content' or 'search_gmail_messages' that read rather than create content. It further specifies support for 'both new drafts and reply drafts', providing precise scope.

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 description provides clear context for usage by explaining that it supports 'new drafts and reply drafts', with examples showing different scenarios. However, it does not explicitly state when to use this tool versus alternatives (e.g., no mention of sibling tools like 'modify_gmail_message_labels' or 'search_gmail_messages'), missing explicit exclusions or comparisons.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/c0webster/hardened-google-workspace-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server