Skip to main content
Glama
unosend

Unosend MCP Server

Official
by unosend

send_email

Send emails through the Unosend API with HTML/text content, CC/BCC, reply-to addresses, and scheduling options for automated communication.

Instructions

Send an email using Unosend API. Supports HTML/text content, CC/BCC, reply-to, and scheduling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesRecipient email address (or comma-separated list)
subjectYesEmail subject line
htmlNoHTML content of the email
textNoPlain text content (used if html not provided)
fromNoSender email (must be from verified domain)
ccNoCC recipient(s), comma-separated
bccNoBCC recipient(s), comma-separated
reply_toNoReply-to email address
scheduled_atNoISO 8601 datetime to schedule (e.g., "2026-01-28T10:00:00Z")
Behavior2/5

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

With no annotations, the description carries full burden but lacks critical behavioral details. It mentions scheduling and content types but omits information on permissions, rate limits, error handling, or what happens upon sending (e.g., confirmation, ID return). This is inadequate for a mutation tool with zero annotation coverage.

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 front-loaded with the core purpose and efficiently lists key features in a single sentence. It avoids redundancy but could be slightly more structured by explicitly stating required parameters or common use cases.

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

Completeness2/5

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

For a mutation tool with 9 parameters, no annotations, and no output schema, the description is incomplete. It fails to address behavioral aspects like authentication needs, side effects, or response format, leaving significant gaps for an AI agent to invoke it correctly.

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 all 9 parameters. The description adds minimal value by listing features like HTML/text content and scheduling, which align with parameters but do not provide additional semantic context beyond what the schema already specifies.

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 specific action ('Send an email') and resource ('using Unosend API'), distinguishing it from sibling tools like send_sms or get_email. It specifies the core functionality with supporting features, making the purpose unambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like send_sms or cancel_email. The description lists features but does not mention prerequisites, such as needing a verified domain for the 'from' field, or contextual cues for selection among siblings.

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/unosend/mcp-server'

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