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mcp-openai-image-generation

mcp-openai-image-generation

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platform.openai.comAI & Agents3Updated 55w ago
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About mcp-openai-image-generation

mcp-openai-image-generation is an MCP server for OpenAI image generation. Its README provides a brief description and a configuration example.

Key features

  1. 01OpenAI image generation

Use cases

  1. 01Configure image generation in an MCP client

MCP support

It is an MCP server configured for clients; the README shows stdio startup and use of OPENAI_API_KEY with an optional OPENAI_BASE_URL.

#mcp#openai#image-generation

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "openai-image-generation": {
      "command": "uvx",
      "args": [
        "mcp-openai-image-generation@latest"
      ],
      "env": {
        "OPENAI_API_KEY": "<OPENAI_API_KEY>",
        "OPENAI_BASE_URL": "<OPENAI_BASE_URL>"
      }
    }
  }
}
Run commanduvx mcp-openai-image-generation@latest
Environment variables to set
OPENAI_API_KEYSecret
OPENAI_BASE_URL

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypimcp-openai-image-generation@latest

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

mcp-openai-image-generation

Release Commit activity License

OpenAI image generation MCP server

Configuration

{
  "mcpServers": {
    "openai-image-generation": {
      "command": "uvx",
      "args": ["mcp-openai-image-generation@latest", "stdio"],
      "env": {
        "OPENAI_API_KEY": "${OPENAI_API_KEY}",
        "OPENAI_BASE_URL": "${OPENAI_BASE_URL}"
      }
    }
  }
}

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.