AI image generation and editing with prompt optimization and quality presets
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Image MCP Server is an MCP server that AI image generation and editing with prompt optimization and quality presets. Its tool list has not been published yet over stdio and http, requires no API key, and scores 91/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"mcp-image": {
"env": {
"GEMINI_API_KEY": "your_gemini_api_key_here",
"IMAGE_OUTPUT_DIR": "/absolute/path/to/images"
},
"args": [
"-y",
"mcp-image"
],
"command": "npx"
}
}
}Are you the author?
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AI image generation and editing with prompt optimization and quality presets
Run this in your terminal to verify the server starts. Then let us know if it worked - your result helps other developers.
npx -y 'mcp-image' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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No known CVEs.
Checked mcp-image against OSV.dev.
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Generate and edit images from Codex, Cursor, Claude Code, or any MCP client. mcp-image adds visual direction to your request before sending it to Gemini, OpenAI, or BytePlus Seedream.
Tell it what image to create or what to change in an existing image, and what it is for. The result is saved to disk and returned to your assistant.
Before generating an image, mcp-image rewrites short requests into more specific prompts. It keeps what you asked for and fills in what the image needs for its use, such as lighting and camera angle for a photo or layout for a poster. Text you want in the image stays as you wrote it, in your language. The more detail you provide, the less it changes.
You ask:
"A photo of a roast chicken dinner for a recipe site. It should look like it was actually cooked, and it should be partway through being carved so you can tell how juicy it is."
mcp-image sends to the image model:
"... a freshly roasted whole chicken resting on a rustic, seasoned wooden carving board. The chicken features deeply bronzed, blistered, and crispy skin ... It is partway carved, with one breast cleanly sliced open to reveal tender, steaming-hot white meat glistening with natural juices pooling slightly onto the board ... shallow depth of field with a softly blurred background."

Generated with Gemini using the default fast quality preset.
What carried through:
for a recipe site: one clear subject, with everything else kept subordinateactually cooked: blistered, uneven browning, rising steam, and drippings on the knifepartway through being carved: one breast sliced open, with the cut piece still resting against the birdhow juicy it is: juices pooling on the board and shallow depth of field around the cut
Baseline from the same request, with prompt enhancement disabled.
Set SKIP_PROMPT_ENHANCEMENT=true to send the original prompt to the image model unchanged.
You need Node.js 22 or later, an MCP-compatible client, and an API key for one image provider.
All three providers generate and edit images. Gemini is the default and requires the least configuration.
| Provider | Image size | Output format | Setup |
|---|---|---|---|
| Gemini (default) | 1K, 2K, 4K | Automatic | Get a key, then set GEMINI_API_KEY |
| OpenAI | 1K, 2K, 4K | PNG or JPEG | Get a key, then set IMAGE_PROVIDER=openai and OPENAI_API_KEY |
| BytePlus Seedream | 1K, 2K | PNG or JPEG | Get an AP region key, then set IMAGE_PROVIDER=seedream and ARK_API_KEY |
Google Search grounding is available with Gemini only. OpenAI may require organization verification before it can generate images.
The examples below use Gemini. Replace the provider settings if you prefer OpenAI or Seedream.
Add this to ~/.codex/config.toml:
[mcp_servers.mcp-image]
command = "npx"
args = ["-y", "mcp-image"]
[mcp_servers.mcp-image.env]
GEMINI_API_KEY = "your_gemini_api_key_here"
IMAGE_OUTPUT_DIR = "/absolute/path/to/images"
Add this to ~/.cursor/mcp.json for all projects, or `.cursor/mcp