mcp-media-engine

generate_email_header_image

Create AI-generated header images for marketing emails and newsletters from subject line and body text. Accepts tone and brand style hints to stay on-brand.

Instructions

Create an AI-generated header image for marketing emails and newsletters. Optimised for wide-format email banners (typically 600px wide) from subject line and body text. Accepts tone and brand_style hints to stay on-brand. Returns a queued media job whose result URL can be embedded in the email template. Use this to create email graphics, newsletter banners, or promotional header visuals.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "generate_email_header_image"
  }
}

Input Schema

Name	Required	Description
`size`	No	Output image dimensions. Defaults to 1024x1024.
`tone`	No	Desired emotional tone (e.g. "professional", "playful", "urgent"). Optional.
`title`	No	Title of the article, email, or post. Used to derive visual style and subject.
`summary`	No	Short summary or body text to guide image composition. If omitted, title alone is used.
`brand_style`	No	Brand aesthetic descriptor (e.g. "minimalist dark", "bold colorful"). Optional.
`aspect_ratio`	No	Explicit aspect ratio override (e.g. "16:9", "1:1", "4:5"). Optional.
`content_type`	No	Type of content this image supports (blog, newsletter, email, social). Defaults to blog.
`target_platform`	No	Platform this image targets, used to pick aspect ratio and style conventions.
`reference_images`	No	Optional reference images with roles (e.g. brand logo, style reference).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jun 17, 2026

TDQS

A4.1/5.0

Behavior4/5

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

The description discloses that the tool returns a 'queued media job' whose result URL can be embedded in email templates, which is critical behavioral information beyond the input schema. It does not mention authentication, rate limits, or potential destructive actions, but given no annotations, this level of detail is adequate.

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, starting with purpose, then optimization, then parameters, and ending with usage. It is concise at 5 sentences with no unnecessary repetition, though it could be slightly tighter.

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?

The description explains the output is a queued job and mentions that the result URL can be embedded, which is essential for integration. It covers tone and brand style hints, and the 9 parameters are all described in the schema. It does not elaborate on job status or error handling, but sibling tools (get_job_status, wait_for_job) cover that gap.

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 baseline is 3. The description adds minimal extra meaning beyond the schema (e.g., mentioning '600px wide' implies default aspect ratio concerns, but not explicitly tied to parameters). The description does not significantly enhance understanding of parameter behavior or dependencies.

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's purpose: 'Create an AI-generated header image for marketing emails and newsletters.' It specifies the resource (email header image) and verb (generate), and distinguishes from siblings by mentioning optimization for wide-format email banners (600px wide), contrasting with tools like generate_social_teaser_image or generate_article_hero_image.

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 usage context: 'Use this to create email graphics, newsletter banners, or promotional header visuals.' However, it does not explicitly state when not to use this tool or compare it to alternatives, leaving some ambiguity about selection criteria among sibling tools.

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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