Generates images using Replicate's Stable Diffusion model and provides tools for saving and managing them.
Generates images using Replicate's Stable Diffusion model and provides tools for saving and managing them. The image generator mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 8 defined tools rather than through you.
An MCP server that uses Replicate to generate images and allows users to save them.
Everything the assistant can do here goes through one of these:
generate-image — Generates an image using Replicate's Stable Diffusion modelsave-image — Saves a generated image to the local filesystemlist-saved-images — Lists all saved imagesResources — The server implements an image storage system with: - Custom image:// URI scheme for accessing individual generated images - Each image resource hasPrompts — The server provides a single prompt: - generate-image: Creates prompts for generating images using Stable Diffusion - Optional "style" argument toTools — The server implements three tools: - generate-image: Generates an image using Replicate's Stable Diffusion model - Takes "prompt" as a requiredUsage — 1. Generate an image by using the "generate-image" tool with a descriptive prompt 2. Save the generated image using the "save-image" tool with theDebugging — Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the [MCPYou will need 2 environment variables: REPLICATE_API_TOKEN, UV_PUBLISH_TOKEN. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Installation goes through your MCP client rather than a global install: point it at @modelcontextprotocol/inspector on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Image Generator's toolset — generate-image, save-image, list-saved-images and 5 more — is a fair guide to whether it matches your workflow. It is maintained by rmcendarfer2017; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| generate-image | Generates an image using Replicate's Stable Diffusion model |
| save-image | Saves a generated image to the local filesystem |
| list-saved-images | Lists all saved images |
| Resources | The server implements an image storage system with: - Custom image:// URI scheme for accessing individual generated images - Each image resource has a name based on its prompt, description with creation date, and image/p |
| Prompts | The server provides a single prompt: - generate-image: Creates prompts for generating images using Stable Diffusion - Optional "style" argument to control the image style (realistic/artistic/abstract) - Generates a promp |
| Tools | The server implements three tools: - generate-image: Generates an image using Replicate's Stable Diffusion model - Takes "prompt" as a required string argument - Optional parameters include "negative_prompt", "width", "h |
| Usage | 1. Generate an image by using the "generate-image" tool with a descriptive prompt 2. Save the generated image using the "save-image" tool with the image URL and prompt 3. View all saved images using the "list-saved-image |
| Debugging | Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector). |
"mcpServers": {
"image-generator": {
"command": "uv",
"args": [
"--directory",
"B:\NEWTEST\image-generator",
"run",
"image-generator"
]
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| REPLICATE_API_TOKEN | Credential the server authenticates with. | Yes |
| UV_PUBLISH_TOKEN | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.