ImageForge MCP

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A lightweight TypeScript MCP server for generating and editing images with gpt-image-2 through the OpenAI Images API.

• Text-to-image requests use POST /v1/images/generations.

• Image editing and reference-image generation use multipart POST /v1/images/edits.

• Generated images are returned as native MCP image content blocks and can optionally be saved locally.

Features

• Model: gpt-image-2

• MCP tools: generate_image and edit_image

• Text-to-image generation

• Image generation guided by one or more reference images

• Editing one or more existing images

• Local absolute paths and HTTP(S) URLs as image inputs

• PNG, JPEG, and WebP input and output

• Up to 16 input images, with a 50 MB limit per image

• Optional local output path with automatic parent-directory creation

• Safe URL validation against loopback, link-local, and private network targets

• stdio transport

Related MCP server: openai-gpt-image-1-mcp

OpenAI-compatible CPA and gateway support

ImageForge MCP works with OpenAI and with CPA, relay, or proxy services that implement a compatible OpenAI Images API. This includes deployments based on projects such as New API, CLI Proxy API, and similar OpenAI-compatible gateways.

Compatibility depends on the gateway implementation rather than its product name:

• Text-to-image requires POST /v1/images/generations.

• Reference-image generation and editing require multipart POST /v1/images/edits with image[] file forwarding.

• Responses must include Base64 image data in data[0].b64_json.

• The configured model name must accept gpt-image-2.

A gateway that only implements /v1/images/generations can be used for text-to-image generation, but not for reference-image generation or editing.

Requirements

• Node.js 22 or later

• An OpenAI API key or a token issued by a compatible CPA/gateway

Install and build

npm install
npm run build

MCP client configuration

For production use, start the published npm package with npx. No repository clone or local build is required. Inject credentials through the MCP client environment:

{
  "mcpServers": {
    "imageforge": {
      "command": "npx",
      "args": ["-y", "imageforge-mcp"],
      "env": {
        "OPENAI_API_KEY": "your-token",
        "OPENAI_IMAGE_MODEL": "gpt-image-2"
      }
    }
  }
}

-y allows npx to download or update the package without an interactive install prompt. Pin a specific version when reproducible deployments are required, for example "imageforge-mcp@0.3.0".

OPENAI_BASE_URL is optional. When it is unset, ImageForge MCP uses the official OpenAI endpoint https://api.openai.com/v1. Set it only when using New API, CLI Proxy API, or another OpenAI-compatible gateway:

"OPENAI_BASE_URL": "https://your-openai-compatible-gateway.example/v1"

The value must point to the gateway's /v1 root. ImageForge MCP appends /images/generations or /images/edits as required.

Do not commit real API keys to Git or write them into shared configuration files.

Codex local development configuration

Create a project-scoped .codex/config.toml using paths that match your machine:

[mcp_servers.imageforge_dev]
command = "/absolute/path/to/node"
args = ["/absolute/path/to/ImageForgeMCP/dist/index.js"]
cwd = "/absolute/path/to/ImageForgeMCP"
env_vars = ["OPENAI_API_KEY", "OPENAI_BASE_URL", "OPENAI_IMAGE_MODEL"]
startup_timeout_sec = 10
tool_timeout_sec = 300
enabled = true
required = false

Export the environment variables before starting Codex:

export OPENAI_API_KEY="your-gateway-token"
export OPENAI_BASE_URL="https://your-openai-compatible-gateway.example/v1"
export OPENAI_IMAGE_MODEL="gpt-image-2"

cd /absolute/path/to/ImageForgeMCP
codex app

Codex loads project-scoped .codex/config.toml only for trusted projects. After adding or changing the MCP configuration, restart Codex or open a new task, then use /mcp verbose to confirm that imageforge_dev exposes:

• generate_image

• edit_image

After changing the TypeScript source, rebuild dist/index.js and restart the task using the MCP server:

npm run build

See the official Codex MCP documentation for all configuration options.

generate_image

Without reference_images, the tool uses /images/generations. With reference images, it uploads them as multipart image[] files to /images/edits.

edit_image

edit_image uses the same model, API, output, and local-save parameters as generate_image, but requires input_images:

Local images are read directly. URL images are downloaded and validated before upload. URLs resolving to loopback, link-local, or private addresses are rejected.

Configuration precedence is: tool arguments, environment variables, then built-in defaults.

When output_path is supplied, ImageForge MCP returns the native MCP image content block, saves the decoded image, and includes the final absolute path in a text content block. Missing parent directories are created automatically. Existing files are not overwritten.

Some OpenAI-compatible gateways may return dimensions different from the requested size; the actual returned file dimensions are authoritative.

Verification

npm test
npm run check

Tests use a local HTTP mock. They do not call a real image API or incur generation charges.

License

MIT

中文说明

ImageForge MCP 是一个轻量的 TypeScript MCP 图片生成与编辑服务，通过 OpenAI Images API 调用 gpt-image-2。

• 纯文本生图调用 POST /v1/images/generations。

• 图片编辑和参考图生图调用 multipart POST /v1/images/edits。

• 生成结果以原生 MCP image 内容块返回，也可以同时保存到本地。

功能

• 模型：gpt-image-2

• MCP 工具：generate_image、edit_image

• 支持纯文本生图

• 支持一张或多张参考图引导生图

• 支持一张或多张图片编辑

• 输入图片支持本地绝对路径和 HTTP(S) URL

• 输入与输出支持 PNG、JPEG、WebP

• 最多 16 张输入图片，每张不超过 50 MB

• 支持通过 output_path 保存到本地，并自动创建父目录

• URL 安全校验，拒绝访问环回、链路本地和私有网络地址

• stdio Transport

OpenAI 兼容 CPA 与网关

ImageForge MCP 不仅支持 OpenAI 官方接口，也支持实现了 OpenAI Images API 兼容协议的 CPA、中转或代理服务，包括基于 New API、CLI Proxy API 等项目部署的 OpenAI 兼容网关。

是否兼容取决于网关实现的接口能力，而不是产品名称：

• 纯文本生图需要实现 POST /v1/images/generations。

• 参考图生图和图片编辑需要实现 multipart POST /v1/images/edits，并正确转发 image[] 文件。

• 响应需要在 data[0].b64_json 中返回 Base64 图片数据。

• 网关需要接受 gpt-image-2 模型名。

如果网关只实现了 /v1/images/generations，仍可用于纯文本生图，但不能使用参考图生图和图片编辑。

环境要求

• Node.js 22 或更高版本

• OpenAI API Key，或 OpenAI 兼容 CPA/网关签发的令牌

安装与构建

npm install
npm run build

MCP 客户端配置

生产环境推荐直接通过 npx 启动 npm 官方包，无需克隆仓库或在本地构建。通过 MCP 客户端环境变量注入密钥：

{
  "mcpServers": {
    "imageforge": {
      "command": "npx",
      "args": ["-y", "imageforge-mcp"],
      "env": {
        "OPENAI_API_KEY": "你的令牌",
        "OPENAI_IMAGE_MODEL": "gpt-image-2"
      }
    }
  }
}

-y 允许 npx 在没有交互式安装提示的情况下下载或更新包。如果部署需要固定版本，可将包名写成 "imageforge-mcp@0.3.0"。

OPENAI_BASE_URL 是可选配置。不设置时，ImageForge MCP 默认使用 OpenAI 官方接口 https://api.openai.com/v1。只有使用 New API、CLI Proxy API 或其他 OpenAI 兼容网关时才需要设置：

"OPENAI_BASE_URL": "https://你的-OpenAI-兼容网关域名/v1"

地址应填写到网关的 /v1 根路径为止，服务会根据请求追加 /images/generations 或 /images/edits。

不要把真实 API Key 写入 Git 或其他共享配置文件。

Codex 本地开发配置

根据本机路径创建项目级 .codex/config.toml：

[mcp_servers.imageforge_dev]
command = "/你的/node/绝对路径"
args = ["/你的/ImageForgeMCP/绝对路径/dist/index.js"]
cwd = "/你的/ImageForgeMCP/绝对路径"
env_vars = ["OPENAI_API_KEY", "OPENAI_BASE_URL", "OPENAI_IMAGE_MODEL"]
startup_timeout_sec = 10
tool_timeout_sec = 300
enabled = true
required = false

启动 Codex 前设置环境变量：

export OPENAI_API_KEY="你的网关令牌"
export OPENAI_BASE_URL="https://你的-OpenAI-兼容网关域名/v1"
export OPENAI_IMAGE_MODEL="gpt-image-2"

cd /你的/ImageForgeMCP/绝对路径
codex app

Codex 只会加载已信任项目中的 .codex/config.toml。新增或修改 MCP 配置后，需要重新启动 Codex 或新建任务，再使用 /mcp verbose 确认 imageforge_dev 提供以下工具：

• generate_image

• edit_image

修改 TypeScript 源码后，需要重新构建并重启使用该 MCP 的任务：

npm run build

完整配置说明见 Codex MCP 官方文档。

generate_image

不传 reference_images 时调用 /images/generations；传入参考图时，将图片作为 multipart image[] 文件上传到 /images/edits。

edit_image

edit_image 与 generate_image 使用相同的模型、API、输出和本地保存参数，但 input_images 必填：

本地图片会直接读取；URL 图片会经过下载和安全校验后再上传。解析到环回、链路本地或私有地址的 URL 会被拒绝。

配置优先级为：工具参数、环境变量、内置默认值。

传入 output_path 时，服务会在返回原生 MCP 图片内容块的同时保存文件，并在文本内容块中返回最终绝对路径。父目录不存在时会自动创建；已有文件不会被覆盖。

部分 OpenAI 兼容网关可能不会严格遵循请求中的 size，应以实际返回文件的尺寸为准。

验证

npm test
npm run check

测试使用本地 HTTP mock，不会调用真实图片 API，也不会产生生图费用。

许可证

MIT