Agent-readable component catalog
The agent can read a live catalog of 27 component types, including properties, defaults, styles, and sample JSON generated from the renderer’s shared registry.
Imejis
Imejis is an image-generation API and remote MCP design server that lets compatible AI agents create, edit, preview, and render structured designs. It helps developers and automation builders turn prompts, templates, and data into images through MCP, API calls, or workflow tools.
AI-driven image generation and design automation
Imejis is an image-generation API and remote Model Context Protocol (MCP) server that gives compatible AI agents a structured design workflow. Agents such as Claude, ChatGPT MCP connectors, Cursor, or custom MCP clients can discover available components, create or modify designs, preview them, and render finished assets.
The service is intended for workflows where an agent or automation needs to turn copy and data into consistent visual output. Designs can be created from templates or from scratch, while render URLs accept field overrides for repeated outputs such as personalized certificates, charts, branded social images, and other data-driven graphics.
Core capabilities
Structured design creation and editing
Create designs from scratch or from templates, then update text, images, charts, QR codes, tables, and shapes as structured JSON rather than relying on screenshots or manual editing.
Preview and export
Use preview_design to inspect a design before delivery, then export the finished image as PNG, JPEG, WebP, or a single-page PDF.
Reusable render URLs
Generate a signed render URL that accepts field overrides and renders fresh per request, allowing one template to serve many data rows or recipients.
Data and design components
The component library covers text, images, QR codes, barcodes, ratings, progress indicators, tables, shapes, and chart types such as bar, line, pie, radar, Sankey, treemap, funnel, and candlestick.
Automation endpoint
The same render endpoint can be called by n8n, Zapier, Make, or scripts using JSON overrides, with examples including workflow-triggered images for email, Slack, or storage.
Practical use cases
Branded social and blog graphics
Ask an MCP client to turn a title, logo, and visual direction into a 1200×630 Open Graph image and export it as a PNG for a blog or campaign page.
Personalized certificates
Create a template with recipient fields and use a render URL to produce a separate certificate for each person by supplying names and dates at request time.
Data-driven reports
Pass structured business or product data into chart, metric, table, or progress components to produce images for reports, dashboards, sales updates, or campaign summaries.
Codes and operational assets
Generate scannable QR codes or barcodes with configurable content and styling for links, coupons, tickets, product identifiers, or shipping materials.
Automated event-based images
Trigger a render from an n8n, Zapier, Make, or scripted workflow when a row, webhook, schedule, lead, sale, or signup changes, then send the returned image to email, Slack, or storage.
Pros and Cons
Pros
- One MCP toolset covers discovery, design creation, editing, previewing, exporting, and asset-related actions.
- The agent and editor use the same registry for 27 component types, reducing discrepancies between available components and render validation.
- Render URLs support reusable templates with per-request field overrides.
- Outputs include PNG, JPEG, WebP, and single-page PDF, and the same endpoint can support no-code or scripted automation.
- The component catalog includes both common design elements and data visuals such as charts, tables, QR codes, barcodes, maps, and timelines.
Cons
- The MCP workflow requires an MCP-enabled client and an OAuth authorization step.
- Render usage is metered against a plan quota or credits, and the free plan has limited renders, designs, public links, and storage.
- The available evidence does not establish broader collaboration or team-management features beyond the listed plan and integration capabilities.
FAQ
How do I connect an AI agent to Imejis?
Imejis provides a remote MCP server at https://api.imejis.io/api/mcp. In a compatible client, add the endpoint as a custom or remote MCP server and authorize Imejis over OAuth. The documented setup flows cover Claude, ChatGPT MCP connectors, and Cursor.
Which AI clients and agents are supported?
The MCP server works with MCP-enabled clients, including Claude Desktop and Code, ChatGPT MCP connectors, Cursor, and custom agents built with the MCP SDK. The agent acts with the permissions granted during OAuth authorization.
What can an agent do after it connects?
An agent can discover the component catalog, create a design or use a template, update structured JSON, preview the result, and export it. Exports can be PNG, JPEG, WebP, or a single-page PDF.
Can I reuse a design with different data?
The get_render_url tool returns a signed URL that renders a design on request and accepts field overrides. This supports a reusable template where values such as names, dates, or other data change for each request.
Is there a free plan?
The free plan includes 100 API renders per month, 50 designs, limited public links, and 500 MB of file storage. Paid plans increase render quotas and storage, with plan details listed on the pricing page.
Quick Facts
- Category
- AI image generation API and MCP design tool
- MCP endpoint
- https://api.imejis.io/api/mcp
- Compatible clients
- Claude, ChatGPT MCP connectors, Cursor, and custom MCP clients
- Component catalog
- 27 component types and 75+ styles
- Export formats
- PNG, JPEG, WebP, and single-page PDF
- Free plan
- 100 API renders per month, 50 designs, and 500 MB file storage
Imejis 대안
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