MCP Midjourney

中期MCP

](https://pypi.org/project/mcp-midjourney/) ](https://pypi.org/project/mcp-midjourney/)   

A. 模型上下文协议（MCP） 用于AI图像和视频生成的服务器 中途 通过 AceDataCloud API.

直接从Claude、VS Code或任何兼容MCP的客户端生成AI图像、视频并管理创意项目。

特性

• 图像生成 -根据文本提示创建AI生成的图像
• 图像变换 -放大、创建变化、缩放和平移图像
• 图像混合 -将多幅图像组合成创意融合
• 基于参考的生成 -使用现有图像作为灵感
• 图片描述 -获取图像的AI描述（反向提示）
• 图像编辑 -使用文本提示和掩码编辑图像
• 视频生成 -从文本和参考图像创建视频
• 视频扩展 -扩展现有视频以使其更长
• 翻译 -将中文提示翻译成英文
• 任务跟踪 -监控生成进度并检索结果

工具参考

快速开始

1.获取您的API代币

1. 注册地址： AceDataCloud平台
2. 去 API文档页
3. 点击 “收购” 获取您的API令牌
4. 复制令牌以在下面使用

2.使用托管服务器（推荐）

AceDataCloud托管托管MCP服务器-- 无需本地安装.

端点： https://midjourney.mcp.acedata.cloud/mcp

所有请求都需要一个Bearer令牌。使用步骤1中的API令牌。

Claude.ai

直接连接 Claude.ai 使用OAuth-- 不需要API令牌:

1. 转到Claude.ai 设置→ 集成→ 添加更多
2. 输入服务器URL: https://midjourney.mcp.acedata.cloud/mcp
3. 完成OAuth登录流程
4. 开始在对话中使用工具

克劳德桌面版

添加到您的配置(~/Library/Application Support/Claude/claude_desktop_config.json 在macOS上）：

{
  "mcpServers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

光标/风帆

添加到MCP配置(.cursor/mcp.json 或 .windsurf/mcp.json):

{
  "mcpServers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

VS代码（副本）

添加到您的VS代码MCP配置中(.vscode/mcp.json):

{
  "servers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

或安装 Ace数据云MCP扩展 对于VS Code，它通过一键设置捆绑了所有15个MCP服务器。

JetBrains 集成开发环境

1. 首选 设置→ 工具→ AI助手→ 模型上下文协议（MCP）
2. 点击 添加 → 超文本传输协议
3. 粘贴：

{
  "mcpServers": {
    "midjourney": {
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

克劳德代码

Claude Code原生支持MCP服务器：

claude mcp add midjourney --transport http https://midjourney.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

或添加到您的项目 .mcp.json:

{
  "mcpServers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

克莱恩

添加到Cline的MCP设置(.cline/mcp_settings.json):

{
  "mcpServers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

亚马逊Q开发者

添加到MCP配置中：

{
  "mcpServers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Roo代码

添加到Roo Code MCP设置：

{
  "mcpServers": {
    "midjourney": {
      "type": "streamable-http",
      "url": "https://midjourney.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Continue.dev

添加 .continue/config.yaml:

mcpServers:
  - name: midjourney
    type: streamable-http
    url: https://midjourney.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

泽德

添加到Zed的设置中(~/.config/zed/settings.json):

{
  "language_models": {
    "mcp_servers": {
      "midjourney": {
        "url": "https://midjourney.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL测试

# Health check (no auth required)
curl https://midjourney.mcp.acedata.cloud/health

# MCP initialize
curl -X POST https://midjourney.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

3.或在本地运行（替代方案）

如果您更喜欢在自己的计算机上运行服务器：

# Install from PyPI
pip install mcp-midjourney
# or
uvx mcp-midjourney

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-midjourney

# Run (HTTP mode for remote access)
mcp-midjourney --transport http --port 8000

克劳德桌面（本地）

{
  "mcpServers": {
    "midjourney": {
      "command": "uvx",
      "args": ["mcp-midjourney"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker（自托管）

docker pull ghcr.io/acedatacloud/mcp-midjourney:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-midjourney:latest

客户端使用自己的Bearer令牌进行连接——服务器从每个请求中提取令牌 Authorization 头球

可用工具

图像生成

图像编辑

视频

效用

任务

信息

使用示例

从提示符生成图像

User: Create a cyberpunk city at night

Claude: I'll generate a cyberpunk city image for you.
[Calls midjourney_imagine with prompt="Cyberpunk city at night, neon lights, rain, futuristic, detailed --ar 16:9"]

放大图像

User: Upscale the second image

Claude: I'll upscale the top-right image from the grid.
[Calls midjourney_transform with image_id and action="upscale2"]

混合多个图像

User: Blend these two images: [url1] and [url2]

Claude: I'll blend these images together.
[Calls midjourney_blend with image_urls=[url1, url2]]

生成视频

User: Animate this image [url] with gentle movement

Claude: I'll create a video from this image.
[Calls midjourney_generate_video with image_url and prompt="Gentle camera movement, cinematic"]

发电模式

配置

环境变量

命令行选项

mcp-midjourney --help

Options:
  --version          Show version
  --transport        Transport mode: stdio (default) or http
  --port             Port for HTTP transport (default: 8000)

发展

设置开发环境

# Clone repository
git clone https://github.com/AceDataCloud/MidjourneyMCP.git
cd MidjourneyMCP

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # or `.venv\Scripts\activate` on Windows

# Install with dev dependencies
pip install -e ".[dev,test]"

运行测试

# Run unit tests
pytest

# Run with coverage
pytest --cov=core --cov=tools

# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration

代码质量

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools

构建和发布

# Install build dependencies
pip install -e ".[release]"

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

项目结构

MidjourneyMCP/
├── core/                   # Core modules
│   ├── __init__.py
│   ├── client.py          # HTTP client for Midjourney API
│   ├── config.py          # Configuration management
│   ├── exceptions.py      # Custom exceptions
│   ├── server.py          # MCP server initialization
│   ├── types.py           # Type definitions
│   └── utils.py           # Utility functions
├── tools/                  # MCP tool definitions
│   ├── __init__.py
│   ├── describe_tools.py  # Image description tools
│   ├── edits_tools.py     # Image editing tools
│   ├── imagine_tools.py   # Image generation tools
│   ├── info_tools.py      # Information tools
│   ├── task_tools.py      # Task query tools
│   ├── translate_tools.py # Translation tools
│   └── video_tools.py     # Video generation tools
├── prompts/                # MCP prompt templates
│   └── __init__.py
├── tests/                  # Test suite
├── deploy/                 # Deployment configs
│   └── production/
│       ├── deployment.yaml
│       ├── ingress.yaml
│       └── service.yaml
├── .env.example           # Environment template
├── .gitignore
├── CHANGELOG.md
├── Dockerfile             # Docker image for HTTP mode
├── docker-compose.yaml    # Docker Compose config
├── LICENSE
├── main.py                # Entry point
├── pyproject.toml         # Project configuration
└── README.md

API 参考

此服务器包装 AceDataCloud中程API:

• 中途想象API -图像生成
• 中途描述API -图片描述
• 中期任务API -任务查询
• 中途编辑API -图像编辑
• 中途视频API -视频生成
• 中译API -翻译

贡献

欢迎投稿！拜托：

1. 分叉存储库
2. 创建要素分支(git checkout -b feature/amazing)
3. 提交您的更改(git commit -m 'Add amazing feature')
4. 推到分支(git push origin feature/amazing)
5. 打开拉取请求

许可证

MIT许可证-请参阅 许可证 了解详情。

链接

• AceDataCloud平台
• Midtrip官方
• 模型上下文协议
• MCP Python SDK

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用爱制作 AceDataCloud