MCP Server for AI Coding Agents

Give your AI coding agents live access to image generation with @inliner/mcp-server. Works with Claude Code, Cursor, GitHub Copilot, Gemini CLI, Windsurf, and any Model Context Protocol compatible tool.

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What is MCP?

The Model Context Protocol (MCP) is an open standard that allows AI assistants to interact with external tools and services. With the Inliner MCP server, your AI coding agent can:

Generate images and save them to your project
Edit existing images with AI instructions
Check your credit usage and plan details
List your projects and generated images
Get recommended dimensions for common use cases

Quick Setup by Platform

Claude Code

claude mcp add inliner -- npx @inliner/mcp-server

OpenAI Codex CLI

Add to ~/.codex/config.toml

[mcp.inliner]
command = "npx"
args = ["@inliner/mcp-server"]

Gemini CLI

Add to ~/.gemini/settings.json

{
  "mcpServers": {
    "inliner": {
      "command": "npx",
      "args": ["@inliner/mcp-server"]
    }
  }
}

Cursor / VS Code

Create .cursor/mcp.json in project root

{
  "mcpServers": {
    "inliner": {
      "command": "npx",
      "args": ["@inliner/mcp-server"],
      "env": { "INLINER_API_KEY": "your-key" }
    }
  }
}

Windsurf

Add to Windsurf MCP settings

{
  "mcpServers": {
    "inliner": {
      "command": "npx",
      "args": ["@inliner/mcp-server"],
      "env": { "INLINER_API_KEY": "your-key" }
    }
  }
}

GitHub Copilot

Add to VS Code MCP settings

{
  "mcpServers": {
    "inliner": {
      "command": "npx",
      "args": ["@inliner/mcp-server"]
    }
  }
}

API Key: Generate an API key from Account > API Keys in the Inliner dashboard. Use the env field in MCP configuration for better compatibility with all clients.

Available Tools

generate_image_url

Build a properly formatted Inliner image URL from description, dimensions, and project

generate_image

Generate an image, poll until ready, and optionally save to a local file

create_image

Quick alias for generating images with sensible defaults (800x600 PNG)

edit_image

Edit an existing image by URL or upload a local image, apply edits, and save

get_projects

List all your Inliner projects with namespaces and settings

create_project

Create a new project and reserve a namespace for image generation

get_project_details

Get detailed project config: namespace, custom prompt, reference images

get_usage

Check remaining credits (image, edit, infill, enhance)

get_current_plan

View current subscription plan and feature allocations

list_images

List generated images with optional project filter

get_image_dimensions

Get recommended dimensions for common use cases (hero, product, profile, etc.)

Example Interactions

Once installed, you can talk to your AI agent naturally:

"Add a hero image to the landing page for my acme-corp project"

I'll generate a hero image for your landing page. Let me get your project details and create the image...

<img src="https://img.inliner.ai/acme-corp/hero-landing-page-modern-saas_1920x1080.png" alt="Modern SaaS landing page hero" />

"Generate a happy duck image and save it to ./images/duck.png"

I'll generate that image and save it to your project. Polling until ready...

Done! Image saved to ./images/duck.png

"Edit this local photo to remove the background and resize to 400x400"

I'll upload the file, apply the background removal edit, resize to 400x400, and save the result...

Done! The edited image has been saved.

"How many image credits do I have left?"

You have 847 image credits remaining this month (out of 1200 on your Pro plan), plus 92 edit credits and 180 infill credits.

"Create a new project called my-portfolio for my personal website"

I'll create that project for you...

Done! Project 'my-portfolio' has been created. You can now use it for generating images with --project my-portfolio or in URLs like https://img.inliner.ai/my-portfolio/...

Resources

The MCP server also provides resources that agents can reference:

inliner://guide - Quick reference for URL format, dimensions, and style hints

Pro Tip: The MCP server works alongside the CLI tool. Use the CLI for batch processing and scripts, and the MCP server for interactive AI-assisted development.