Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/dvdxfv/douyin-mcp-servernpx agentmods add skills/dvdxfv/douyin-mcp-server/douyin-videoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dvdxfv/douyin-mcp-server/douyin-video)<a href="https://agentmods.dev/skills/dvdxfv/douyin-mcp-server/douyin-video"><img src="https://agentmods.dev/badge/skills/dvdxfv/douyin-mcp-server/douyin-video/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dvdxfv/douyin-mcp-server/douyin-video"><img src="https://agentmods.dev/badge/skills/dvdxfv/douyin-mcp-server/douyin-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.01245 |
| Opus 5.5 | $0.00020 | $0.00498 |
| Sonnet 5.5 | $0.00010 | $0.00249 |
| Haiku 4.5 | $0.00005 | $0.00125 |
Grade A, and why
douyin-video scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
抖音无水印视频下载和文案提取
从抖音分享链接获取媒体,使用本机语音识别生成逐字稿,再整理成可用口播文案。
功能概述
- 获取下载链接: 从抖音分享链接解析出无水印视频的直接下载地址 (无需 API 密钥)
- 下载视频: 将无水印视频下载到本地指定目录
- 浏览器降级: HTTP 解析失败时自动使用共享 Playwright 捕获签名音频
- 本地转写: 使用
faster-whisper-medium / CPU int8,不消耗 ASR API - 整理口播: 使用 DeepSeek 去重复、补标点和结构,不虚构内容
- 自动保存: 每个视频的文案自动保存到独立文件夹 (视频ID为文件夹名)
环境要求
依赖安装
uv sync --extra web
系统要求
- FFmpeg/ffprobe 必须可用
- Windows 浏览器降级使用
D:\AI_Tools\bin\playwright-node.cmd - 模型权重默认读取
D:\AI_Tools\models\huggingface\hub
API 密钥配置
本地 ASR 不需要密钥;最后的口播整理需要设置:
set DOUYIN_DEEPSEEK_API_KEY=your-deepseek-api-key
密钥只放环境变量,不写入仓库和运行报告。
使用方法
方法一: 使用脚本 (推荐)
# 获取视频信息和下载链接 (无需 API 密钥)
python scripts/douyin_downloader.py --link "抖音分享链接" --action info
# 下载视频到指定目录
python scripts/douyin_downloader.py --link "抖音分享链接" --action download --output ./videos
# 提取逐字稿并整理口播 (需要 DOUYIN_DEEPSEEK_API_KEY)
python scripts/douyin_downloader.py --link "抖音分享链接" --action extract --output ./output
# 安静模式 (减少输出)
python scripts/douyin_downloader.py --link "抖音分享链接" --action extract --output ./output --quiet
输出目录结构
提取文案后, 每个视频会保存到独立文件夹:
output/
├── 7600361826030865707/ # 视频ID为文件夹名
│ ├── audio.m4a # 已校验的完整音频
│ ├── transcript-raw.md # 本机 ASR 原始逐字稿
│ ├── copy.md # DeepSeek 整理后的口播
│ ├── metadata.json
│ └── run-report.json # 五阶段状态和验证证据
├── 7581044356631612699/
│ └── ...
└── ...
方法二: 在 Python 代码中调用
from scripts.douyin_downloader import get_video_info, download_video, extract_text
# 获取视频信息
info = get_video_info("抖音分享链接")
print(f"视频ID: {info['video_id']}")
print(f"标题: {info['title']}")
print(f"下载链接: {info['url']}")
# 下载视频
video_path = download_video("抖音分享链接", output_dir="./videos")
# 提取文案并保存到文件
result = extract_text("抖音分享链接", output_dir="./output")
print(f"文案已保存到: {result['output_path']}")
print(result['text'])
工作流程
获取视频信息
- 解析抖音分享链接, 提取真实的视频 URL
- 模拟移动端请求获取页面数据
- 从页面 JSON 数据中提取无水印视频地址
- 返回视频 ID, 标题和下载链接
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 139 lines · 50 tokens per session scan A 12907e2025f4
douyin-video is a skill published in the GitHub repository dvdxfv/douyin-mcp-server (1 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 50 tokens to every session and 1,245 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
douyin-video compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| douyin-videodvdxfv/douyin-mcp-server | Skill | 1 | 2mo ago | Apache-2.0 | A | 50 | Claude Code, Codex |
| patent-maphandsomestWei/patent-disclosure-skill | Skill | 13k | today | MIT | A | 48 | Claude Code |
| autoreviewopenclaw/clawhub | Skill | 9.6k | today | MIT | A | 17 | Claude Code, Codex |
| sandbaseiflytek/skillhub | Skill | 5.4k | 2d ago | Apache-2.0 | A | 67 | Claude Code |
| convex-insightsopenclaw/clawhub | Skill | 9.6k | today | MIT | A | 45 | Claude Code, Codex |
| convex-addopenclaw/clawhub | Skill | 9.6k | today | MIT | A | 81 | Claude Code, Codex |
| openclaw-design-systemopenclaw/clawhub | Skill | 9.6k | today | MIT | A | 37 | Claude Code, Codex |