CapCutAPI：开源剪映编程控制与视频编辑方案

# 最低要求
操作系统：Windows 10+, macOS 11+, Ubuntu 18.04+
Python 版本：3.10+
内存：8GB RAM
存储：2GB 可用空间
FFmpeg: 最新稳定版

# 推荐配置
操作系统：Windows 11, macOS 13+, Ubuntu 22.04+
Python 版本：3.11+
内存：16GB+ RAM
存储：SSD, 10GB+ 可用空间
FFmpeg: 带硬件加速版本
GPU: 支持 CUDA 或 Metal 的显卡（可选）

2. 安装步骤

基础安装：

# 1. 克隆仓库
git clone https://github.com/sun-guannan/CapCutAPI.git
cd CapCutAPI

# 2. 创建虚拟环境（推荐）
python -m venv venv-capcut

# 激活环境（Linux/macOS）
source venv-capcut/bin/activate
# 激活环境（Windows）
venv-capcut\Scripts\activate

# 3. 安装依赖
pip install -r requirements.txt

# 安装 MCP 协议支持（可选）
pip install -r requirements-mcp.txt

# 4. 配置设置
cp config.json.example config.json
# 编辑 config.json 文件配置参数

Docker 方式安装：

# Dockerfile 示例
FROM python:3.11-slim
WORKDIR /app
# 安装系统依赖
RUN apt-get update && apt-get install -y \
    ffmpeg \
    libsm6 \
    libxext6 \
    && rm -rf /var/lib/apt/lists/*
# 复制项目文件
COPY . .
# 安装 Python 依赖
RUN pip install -r requirements.txt
# 暴露端口
EXPOSE 9001
# 启动服务
CMD ["python", "capcut_server.py"]

# 使用 Docker Compose
docker-compose up -d
# 或直接运行
docker build -t capcut-api .
docker run -p 9001:9001 -v $(pwd)/data:/app/data capcut-api

3. 配置详解

配置文件示例：

{
  "server": {
    "host": "0.0.0.0",
    "port": 9001,
    "debug": false,
    "workers": 4
  },
  "storage": {
    "draft_dir": "./drafts",
    "temp_dir": "./temp",
    "max_file_size": "2GB"
  },
  "media": {
    "ffmpeg_path": "/usr/bin/ffmpeg",
    "supported_formats": [
      "mp4", "mov", "avi", "mkv", "mp3", "wav", "flac", "jpg", "png", "gif"
    ],
    "max_resolution": "4096x2160"
  },
  "security": {
    "api_key": "your-secret-key-here",
    "cors_origins": ["*"],
    "rate_limit": "100/minute"
  },
  "logging": {
    "level": "INFO",
    "file": "./logs/capcutapi.log",
    "max_size": "100MB",
    "backup_count": 5
  }
}

环境变量配置：

# 环境变量示例
export CUTAPI_HOST="0.0.0.0"
export CUTAPI_PORT="9001"
export CUTAPI_DEBUG="false"
export FFMPEG_PATH="/usr/bin/ffmpeg"
export DRAFT_DIR="./drafts"
export API_KEY="your-secret-key"
# 或使用.env 文件
echo 'CUTAPI_HOST=0.0.0.0 CUTAPI_PORT=9001 FFMPEG_PATH=/usr/bin/ffmpeg DRAFT_DIR=./drafts' > .env

4. MCP 协议配置

客户端配置：

{
  "mcpServers": {
    "capcut-api": {
      "command": "python3",
      "args": ["mcp_server.py"],
      "cwd": "/path/to/CapCutAPI",
      "env": {
        "PYTHONPATH": "/path/to/CapCutAPI",
        "DEBUG": "0"
      },
      "timeout": 30
    }
  }
}

连接测试：

# 测试 MCP 连接
python test_mcp_client.py
# 预期输出
# ✅ MCP 服务器启动成功
# ✅ 获取到 11 个可用工具
# ✅ 草稿创建测试通过

使用指南

1. 基本使用流程

1. 初始化 API 客户端
2. 创建草稿项目
3. 添加媒体素材
4. 应用编辑效果
5. 导出最终视频

2. API 使用示例

创建新项目：

import requests
import json

# 创建新草稿
def create_draft(width=1080, height=1920):
    url = "http://localhost:9001/create_draft"
    payload = {
        "width": width,
        "height": height,
        "fps": 30,
        "background_color": "#000000",
        "metadata": {
            "title": "我的第一个 API 项目",
            "author": "开发者",
            "description": "使用 CapCutAPI 创建的项目"
        }
    }
    response = requests.post(url, json=payload)
    return response.json()

# 添加视频素材
def add_video(draft_id, video_url, start_time=0, duration=10):
    url = "http://localhost:9001/add_video"
    payload = {
        "draft_id": draft_id,
        "video_url": video_url,
        "start": start_time,
        "end": start_time + duration,
        "volume": 0.8,
        "transition": "fade_in",
        "effects": ["color_correction", "stabilization"]
    }
    response = requests.post(url, json=payload)
    return response.json()

# 添加文本元素
def add_text(draft_id, text, start_time, duration):
    url = "http://localhost:9001/add_text"
    payload = {
        "draft_id": draft_id,
        "text": text,
        "start": start_time,
        "end": start_time + duration,
        "font": "Source Han Sans",
        "font_size": 48,
        "font_color": "#FFD700",
        "background_color": "#00000080",
        "animation": "fade_slide_in"
    }
    response = requests.post(url, json=payload)
    return response.json()

# 使用示例
draft = create_draft(1080, 1920)
draft_id = draft["result"]["draft_id"]
add_video(draft_id, "https://example.com/background.mp4", 0, 10)
add_text(draft_id, "欢迎使用 CapCutAPI", 2, 5)
print(f"项目创建成功！草稿 ID: {draft_id}")

高级编辑功能：

# 添加关键帧动画
def add_keyframe_animation(draft_id, track_name, property_type, times, values):
    url = "http://localhost:9001/add_keyframe"
    payload = {
        "draft_id": draft_id,
        "track_name": track_name,
        "property_type": property_type,
        "times": times,
        "values": values,
        "easing": "ease_in_out"
    }
    response = requests.post(url, json=payload)
    return response.json()

# 添加音频效果
def add_audio_effect(draft_id, audio_url, effects):
    url = "http://localhost:9001/add_audio_effect"
    payload = {
        "draft_id": draft_id,
        "audio_url": audio_url,
        "effects": effects,
        "volume": 0.7,
        "fade_in": 2.0,
        "fade_out": 2.0
    }
    response = requests.post(url, json=payload)
    return response.json()

# 添加视觉特效
def add_visual_effect(draft_id, effect_type, parameters):
    url = "http://localhost:9001/add_effect"
    payload = {
        "draft_id": draft_id,
        "effect_type": effect_type,
        "parameters": parameters,
        "duration": 5.0,
        "intensity": 0.8
    }
    response = requests.post(url, json=payload)
    return response.json()

3. MCP 协议使用

完整工作流示例：

from mcp_client import McpClient

# 初始化 MCP 客户端
client = McpClient("capcut-api")

# 创建新项目
draft = client.call_tool("create_draft", {
    "width": 1080,
    "height": 1920,
    "fps": 30,
    "metadata": {
        "title": "MCP 示例项目",
        "tags": ["demo", "test"]
    }
})
draft_id = draft["result"]["draft_id"]

# 添加多媒体内容
client.call_tool("add_video", {
    "draft_id": draft_id,
    "video_url": "https://example.com/main.mp4",
    "start": 0,
    "end": 15,
    "track": "main_video"
})
client.call_tool("add_audio", {
    "draft_id": draft_id,
    "audio_url": "https://example.com/bgm.mp3",
    "start": 0,
    "end": 30,
    "volume": 0.6
})
client.call_tool("add_text", {
    "draft_id": draft_id,
    "text": "AI 视频生成演示",
    "start": 2,
    "end": 10,
    "style": {
        "font_size": 56,
        "font_color": "#FFFFFF",
        "background": "#00000080"
    }
})

# 添加高级效果
client.call_tool("add_transition", {
    "draft_id": draft_id,
    "type": "crossfade",
    "duration": 1.5,
    "position": 5.0
})
client.call_tool("add_filter", {
    "draft_id": draft_id,
    "filter_type": "cinematic",
    "intensity": 0.7,
    "duration": 15.0
})

# 保存并导出
result = client.call_tool("export_draft", {
    "draft_id": draft_id,
    "format": "mp4",
    "resolution": "1080p",
    "quality": "high"
})
print(f"项目导出完成：{result['result']['output_url']}")

4. 高级功能使用

批量处理示例：

import concurrent.futures

def batch_process_videos(video_list, template_id):
    """批量处理视频项目"""
    results = []
    with concurrent.futures.ThreadPoolExecutor(max_workers=4) as executor:
        futures = []
        for video_data in video_list:
            future = executor.submit(process_single_video, video_data, template_id)
            futures.append(future)
        for future in concurrent.futures.as_completed(futures):
            try:
                result = future.result()
                results.append(result)
            except Exception as e:
                print(f"处理失败：{e}")
    return results

def process_single_video(video_data, template_id):
    """处理单个视频"""
    # 创建新草稿
    draft = create_draft_from_template(template_id)
    draft_id = draft["draft_id"]
    # 添加主要内容
    add_video(draft_id, video_data["video_url"], 0, video_data["duration"])
    add_audio(draft_id, video_data["audio_url"], 0, video_data["duration"])
    # 添加动态文本
    for text_item in video_data["text_elements"]:
        add_text(draft_id, text_item["text"], text_item["start_time"], text_item["duration"])
    # 添加特效
    for effect in video_data["effects"]:
        add_effect(draft_id, effect["type"], effect["parameters"])
    # 导出最终视频
    result = export_draft(draft_id, video_data["output_format"])
    return result

自动化工作流：

def automated_video_workflow(config):
    """全自动视频生成工作流"""
    # 1. 媒体准备
    media_assets = prepare_media_assets(config)
    # 2. 创建项目框架
    draft = create_draft(config["project_settings"])
    draft_id = draft["draft_id"]
    # 3. 添加主要内容
    for asset in media_assets["videos"]:
        add_video(draft_id, asset["url"], asset["start"], asset["duration"])
    for asset in media_assets["audios"]:
        add_audio(draft_id, asset["url"], asset["start"], asset["duration"])
    # 4. 添加文本和图形
    for text in config["text_elements"]:
        add_text(draft_id, text["content"], text["start"], text["duration"])
    for graphic in config["graphics"]:
        add_image(draft_id, graphic["url"], graphic["start"], graphic["duration"])
    # 5. 应用效果和转场
    for effect in config["effects"]:
        add_effect(draft_id, effect["type"], effect["params"])
    for transition in config["transitions"]:
        add_transition(draft_id, transition["type"], transition["position"])
    # 6. 最终渲染
    output = export_project(draft_id, config["output_settings"])
    # 7. 清理资源
    cleanup_temp_files(draft_id)
    return output

应用场景实例

案例 1：社交媒体内容批量生产

场景：营销机构需要为多个客户批量生产社交媒体视频内容

解决方案：

利用模板机制快速填充不同客户的素材和文案，实现规模化生产。

实施代码：

class SocialMediaProducer:
    def __init__(self, api_client):
        self.client = api_client
        self.templates = {}

    def load_template(self, template_name, config):
        """加载生产模板"""
        template = {
            'base_draft': self.create_base_draft(config),
            'media_slots': config.get('media_slots', []),
            'text_slots': config.get('text_slots', []),
            'effects': config.get('effects', []),
            'output_settings': config.get('output', {})
        }
        self.templates[template_name] = template

    def batch_produce(self, template_name, data_list):
        """批量生产视频"""
        results = []
        for data in data_list:
            try:
                # 复制基础草稿
                draft_id = self.duplicate_draft(
                    self.templates[template_name]['base_draft']
                )
                # 填充媒体内容
                for slot in self.templates[template_name]['media_slots']:
                    media_data = data['media'].get(slot['name'])
                    if media_data:
                        self.fill_media_slot(draft_id, slot, media_data)
                # 填充文本内容
                for slot in self.templates[template_name]['text_slots']:
                    text_data = data['text'].get(slot['name'])
                    if text_data:
                        self.fill_text_slot(draft_id, slot, text_data)
                # 应用特效
                for effect in self.templates[template_name]['effects']:
                    self.apply_effect(draft_id, effect)
                # 导出视频
                output = self.export_video(
                    draft_id, self.templates[template_name]['output_settings']
                )
                results.append({
                    'success': True,
                    'output': output,
                    'data': data
                })
            except Exception as e:
                results.append({
                    'success': False,
                    'error': str(e),
                    'data': data
                })
        return results

    def fill_media_slot(self, draft_id, slot, media_data):
        """填充媒体槽位"""
        if slot['type'] == 'video':
            self.client.add_video(
                draft_id, media_data['url'], slot['start_time'], slot['duration'],
                track=slot.get('track', 'main')
            )
        elif slot['type'] == 'audio':
            self.client.add_audio(
                draft_id, media_data['url'], slot['start_time'], slot['duration'],
                volume=slot.get('volume', 1.0)
            )

    def fill_text_slot(self, draft_id, slot, text_data):
        """填充文本槽位"""
        self.client.add_text(
            draft_id, text_data['content'], slot['start_time'], slot['duration'],
            style={
                'font_size': slot.get('font_size', 48),
                'font_color': text_data.get('color', '#FFFFFF'),
                'animation': slot.get('animation', 'fade_in')
            }
        )

生产效益：显著提升生产效率，有效降低制作成本，保持内容一致性，缩短发布时间，实现效果追踪自动化。

案例 2：教育机构课程视频制作

场景：在线教育平台需要为大量课程制作统一风格的视频内容

教育视频模板：

# education_template.yaml
template:
  name: "education_lecture"
  duration: 1800 # 30 分钟
  dimensions: [1920, 1080]
  fps: 30
  tracks:
    main_video:
      type: "video"
      position: "primary"
      default_content: "lecturer_video.mp4"
    presentation:
      type: "video"
      position: "picture_in_picture"
      default_content: "slides.mp4"
      size: [800, 600]
      position: [100, 100]
    background_music:
      type: "audio"
      volume: 0.3
      loop: true
      default_content: "background_music.mp3"
  intro_outro:
    type: "composite"
    elements:
      - type: "video"
        file: "intro.mp4"
        start: 0
        end: 10
      - type: "video"
        file: "outro.mp4"
        start: 1790
        end: 1800
  text_elements:
    title:
      type: "text"
      start: 10
      end: 20
      content: "课程标题"
      style:
        font_size: 72
        font_color: "#FFFFFF"
        background: "#00000080"
        animation: "zoom_in"
    chapter_title:
      type: "text"
      position: "top_center"
      duration: 5
      style:
        font_size: 48
        font_color: "#4A90E2"
        shadow: true
  watermark:
    type: "text"
    start: 0
    end: 1800
    content: "© 教育机构名称"
    position: [50, 50]
    style:
      font_size: 24
      font_color: "#FFFFFF80"
  effects:
    transition_between_slides:
      type: "transition"
      trigger: "slide_change"
      effect: "crossfade"
      duration: 1.5
    highlight_key_points:
      type: "effect"
      effect: "highlight"
      parameters:
        color: "#FFFF00"
        size: 1.2
        duration: 3
  automation:
    auto_subtitles:
      enabled: true
      source: "audio_track"
      language: "zh-CN"
      style: "education"
    slide_sync:
      enabled: true
      source: "presentation_track"
      detect_slide_changes: true

实施代码：

from capcutapi import EducationVideoProducer

# 初始化教育视频生成器
producer = EducationVideoProducer(template="education_template.yaml")

# 设置课程内容
course_data = {
    "title": "人工智能基础与应用",
    "lecturer_video": "ai_lecture.mp4",
    "slides": "ai_slides.pptx",
    "background_music": "classical_bgm.mp3",
    "chapters": [
        {
            "title": "第一章：机器学习基础",
            "start": 0,
            "duration": 600,
            "key_points": [
                {"text": "监督学习", "time": 120},
                {"text": "无监督学习", "time": 300},
                {"text": "强化学习", "time": 450}
            ]
        },
        {
            "title": "第二章：深度学习原理",
            "start": 600,
            "duration": 600,
            "key_points": [
                {"text": "神经网络结构", "time": 720},
                {"text": "反向传播算法", "time": 900},
                {"text": "卷积神经网络", "time": 1050}
            ]
        },
        {
            "title": "第三章：AI 应用案例",
            "start": 1200,
            "duration": 600,
            "key_points": [
                {"text": "计算机视觉", "time": 1320},
                {"text": "自然语言处理", "time": 1500},
                {"text": "强化学习应用", "time": 1650}
            ]
        }
    ]
}

# 生成课程视频
output_video = producer.generate_course(
    course_data,
    output_format="mp4",
    quality="high",
    output_path="courses/ai_foundations.mp4"
)
print(f"课程视频生成完成：{output_video}")

教育价值：提升课程制作效率，确保视频质量统一标准化，减少教师工作量，提高学生参与度，支持内容快速迭代。

案例 3：电商产品推广视频自动化

场景：电商平台需要为数千种商品自动生成推广视频

实施代码：

from capcutapi import EcommerceVideoGenerator
import pandas as pd

# 初始化电商视频生成器
generator = EcommerceVideoGenerator(
    template="ecommerce_template.yaml",
    media_library="ecommerce_media/",
    voice_library="voices/"
)

# 加载产品数据
products = pd.read_csv("products.csv")

# 批量生成产品视频
for _, product in products.iterrows():
    video_data = {
        "product_id": product["id"],
        "name": product["name"],
        "category": product["category"],
        "price": product["price"],
        "discount": product.get("discount", 0),
        "images": [f"products/{product['id']}_{i}.jpg" for i in range(1, 6)],
        "features": product["features"].split(";"),
        "reviews": [
            {"text": "质量非常好，物超所值", "rating": 5},
            {"text": "包装精美，送货快速", "rating": 4}
        ],
        "promotion": {
            "type": "flash_sale" if product["discount"] > 0 else "normal",
            "end_time": "2024-12-31 23:59:59"
        }
    }
    # 生成视频
    output_file = f"videos/{product['id']}_{product['name']}.mp4"
    generator.generate_video(
        video_data, output_file, voice_over=True, subtitles=True
    )
    print(f"已生成：{product['name']}")
print("所有产品视频生成完成!")

电商效益：大幅降低视频制作成本，提高内容产出速度，提升转化率，实现个性化推荐精准匹配，支持促销活动即时响应。

案例 4：新闻媒体自动化报道

场景：新闻机构需要快速生成视频新闻报道

新闻自动化流程：

from capcutapi import NewsVideoProducer
from news_scraper import NewsAggregator

# 初始化新闻视频生成器
producer = NewsVideoProducer(
    template="news_template.yaml",
    voice="news_anchor_voice.mp3"
)

# 获取新闻数据
aggregator = NewsAggregator()
news_items = aggregator.get_top_news(limit=5)

# 生成新闻报道
for news in news_items:
    # 创建新闻草稿
    draft_id = producer.create_draft(
        title=news["title"],
        category=news["category"],
        duration=news["duration"]
    )
    # 添加内容元素
    producer.add_intro(news["headline"])
    producer.add_video_clip(news["video_url"])
    producer.add_text_overlay(news["summary"])
    if news["location"]:
        producer.add_location_marker(news["location"])
    if news["statistics"]:
        producer.add_infographic(news["statistics"])
    # 添加相关报道
    for related in news["related_stories"]:
        producer.add_related_story(related["title"], related["url"])
    # 添加记者信息
    producer.add_reporter_info(
        name=news["reporter"], contact=news["contact"]
    )
    # 添加结尾
    producer.add_outro("感谢收看")
    # 导出视频
    output_file = f"news/{news['date']}_{news['id']}.mp4"
    producer.export_draft(
        draft_id, output_file, quality="medium", subtitles=True
    )
    print(f"新闻报道生成：{news['title']}")
    # 清理资源
    producer.cleanup()

新闻价值：大幅提高报道速度，减少人力成本，保持内容一致性统一标准，支持多平台适配一键生成，实现突发新闻即时响应。

案例 5：个人创作者内容生产

场景：内容创作者需要高效制作社交媒体视频

创作者工作流：

from capcutapi import CreatorStudio
from content_planner import ContentCalendar

# 初始化创作者工作室
studio = CreatorStudio(
    user_profile="creator_profile.json",
    template_library="templates/"
)

# 加载内容日历
calendar = ContentCalendar()
content_plan = calendar.get_weekly_plan()

# 处理每日内容
for day, content_items in content_plan.items():
    print(f"处理 {day} 的内容:")
    for item in content_items:
        # 选择模板
        template = studio.select_template(
            content_type=item["type"],
            platform=item["platform"],
            style=item["style"]
        )
        # 准备素材
        media = studio.prepare_media(
            item["media_sources"], duration=item["duration"]
        )
        # 生成字幕
        if item["script"]:
            subtitles = studio.generate_subtitles(
                item["script"], voice_over=item["voice_over"]
            )
        # 创建项目
        draft_id = studio.create_draft(
            template=template, duration=item["duration"]
        )
        # 添加内容
        studio.add_media(draft_id, media)
        if item["script"]:
            studio.add_subtitles(draft_id, subtitles)
        # 添加品牌元素
        studio.add_branding(
            draft_id, logo=True, watermark=True, color_scheme=item["brand_colors"]
        )
        # 添加特效
        if item["effects"]:
            for effect in item["effects"]:
                studio.add_effect(draft_id, effect)
        # 导出视频
        output_file = f"output/{day}/{item['title']}.mp4"
        studio.export_video(
            draft_id, output_file, platform=item["platform"], optimize=True
        )
        print(f" - 完成：{item['title']}")
    print(f"{day} 内容生成完成\n")
print("本周所有内容已生成!")

创作者价值：显著提高内容产出，使创意实现更加自由，支持平台适配一键优化，全面保持品牌一致性，提升粉丝互动效率。

社区与支持

1. 贡献指南

项目协作流程：

1. Fork 项目仓库
2. 创建特性分支 (git checkout -b feature/amazing-feature)
3. 提交代码变更 (git commit -m 'Add some amazing feature')
4. 推送到分支 (git push origin feature/amazing-feature)
5. 创建 Pull Request 到 dev 分支

2. 社区资源

3. 支持与联系

• 问题反馈：GitHub Issues
• 功能建议：GitHub Issues

总结

CapCutAPI 作为开源剪映/Jianying API 解决方案，通过其强大的功能和灵活的架构，改变了视频内容创作的方式。它让视频编辑变得可编程化，为 AI 生成内容提供精准控制，解决 AI 视频生成中常见的控制不足问题。该工具已在多个领域证明其价值，适用于内容创作者、教育机构、电商平台、新闻媒体及营销机构等场景，为用户提供强大的视频创作能力。