Media · Local MCP server

Imagine MCP

MCP server for image/video understanding & generation (Gemini/OpenAI/Grok)

What the MCP Registry states

The entry as published to the official MCP Registry (read 2026-10-04), latest version.

Registry name
io.github.n24q02m/imagine-mcp
Version
1.11.6
Status
Active
Category
media
Transport
stdio (local process)
Package
PyPI, OCI image (Docker)
Published
2026-09-12
Updated
2026-09-12
Publisher
n24q02m (GitHub) · 8 servers with pages here
Listed under
OpenAI MCP servers, Gemini MCP servers
Repository
github.com/n24q02m/imagine-mcp.git
Source
Registry API entry

Packages

RegistryPackageVersionTransportEnvironment variables
PyPIruntime: uvximagine-mcp1.11.6stdioUNDERSTAND_MODELS, GEMINI_API_KEY (secret), OPENAI_API_KEY (secret), XAI_API_KEY (secret)
OCI image (Docker)runtime: dockerdocker.io/n24q02m/imagine-mcp:latest—stdioUNDERSTAND_MODELS, GEMINI_API_KEY (secret), OPENAI_API_KEY (secret), XAI_API_KEY (secret)

How to connect Imagine MCP

Imagine MCP runs locally from a Python package published to PyPI: imagine-mcp version 1.11.6. It speaks MCP over stdio, so the client starts it as a program and talks to it through standard input and output. It needs Python; clients usually start it with uvx (from uv) or after pip install — the usual command is uvx imagine-mcp. It reads these environment variables: UNDERSTAND_MODELS, GEMINI_API_KEY (secret), OPENAI_API_KEY (secret) and XAI_API_KEY (secret); set them in the client's configuration for this server.

Imagine MCP runs locally from a container image in an OCI registry such as Docker Hub or GitHub Container Registry: docker.io/n24q02m/imagine-mcp:latest. It speaks MCP over stdio, so the client starts it as a program and talks to it through standard input and output. It needs Docker or another OCI container runtime; started with docker run — the usual command is docker run -i --rm -e UNDERSTAND_MODELS -e GEMINI_API_KEY -e OPENAI_API_KEY -e XAI_API_KEY docker.io/n24q02m/imagine-mcp:latest. It reads these environment variables: UNDERSTAND_MODELS, GEMINI_API_KEY (secret), OPENAI_API_KEY (secret) and XAI_API_KEY (secret); set them in the client's configuration for this server.

In the mcpServers JSON format that many desktop and editor MCP clients read, the entry looks like this (placeholders in angle brackets):

{
  "mcpServers": {
    "imagine-mcp": {
      "command": "uvx",
      "args": [
        "imagine-mcp"
      ],
      "env": {
        "UNDERSTAND_MODELS": "<value>",
        "GEMINI_API_KEY": "<secret>",
        "OPENAI_API_KEY": "<secret>",
        "XAI_API_KEY": "<secret>"
      }
    }
  }
}

Derived from the registry entry, not tested here. What the server does, and on what terms, is set by its publisher; check its repository or website before giving it access to your accounts or files. How to add an MCP server to an assistant · Before you connect

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