youtube-summarizer
Compare original and translation side by side
🇺🇸
Original
English🇨🇳
Translation
ChineseYouTube Summarizer Skill
YouTube Summarizer Skill
Automatically fetch transcripts from YouTube videos, generate structured summaries, and deliver full transcripts to messaging platforms.
自动从YouTube视频中获取字幕,生成结构化摘要,并将完整字幕发送至消息平台。
Why This vs ChatGPT?
为何选择本工具而非ChatGPT?
Problem with ChatGPT: It can't access YouTube transcripts directly. You have to manually copy/paste captions or use a third-party tool first, then feed the text to ChatGPT. Multi-step, clunky, loses video metadata.
This skill provides:
- One-step transcript extraction - Drop a YouTube URL, get the full transcript automatically
- Structured summarization - Consistent format (thesis → insights → takeaway) every time, not random bullet points
- Video metadata included - Title, channel, views, publish date embedded in summary
- Full transcript delivery - Saves timestamped transcript to file and sends to Telegram/chat platforms
- Works from VPS/cloud - Uses Android client emulation to bypass YouTube's cloud IP blocking (where yt-dlp fails)
- Multi-language support - Auto-fetches in requested language with English fallback
You can replicate this by manually enabling captions, copying text, pasting to ChatGPT, reformatting the output, saving to a file, and uploading. Takes 5-10 minutes. This skill does it in 15-20 seconds.
ChatGPT的问题: 它无法直接访问YouTube字幕。你必须先手动复制粘贴字幕或使用第三方工具,再将文本导入ChatGPT。步骤繁琐,还会丢失视频元数据。
本工具的优势:
- 一键提取字幕 - 粘贴YouTube URL,即可自动获取完整字幕
- 结构化摘要生成 - 始终采用统一格式(核心论点→关键见解→行动建议),而非随机的项目符号
- 包含视频元数据 - 摘要中嵌入视频标题、频道、播放量、发布日期
- 完整字幕交付 - 将带时间戳的字幕保存为文件,并发送至Telegram等消息平台
- 支持VPS/云环境 - 通过安卓客户端模拟绕过YouTube的云IP封锁(yt-dlp在此场景下会失效)
- 多语言支持 - 自动获取指定语言的字幕,无对应语言时默认使用英文
手动操作的替代流程: 手动启用字幕、复制文本、粘贴到ChatGPT、重新格式化输出、保存到文件并上传。整个过程需要5-10分钟,而本工具仅需15-20秒。
When to Use
适用场景
Activate this skill when:
- User shares a YouTube URL (youtube.com/watch, youtu.be, youtube.com/shorts)
- User asks to summarize or transcribe a YouTube video
- User requests information about a YouTube video's content
- You need to analyze video content for research or content creation
在以下场景中启用本工具:
- 用户分享YouTube URL(youtube.com/watch、youtu.be、youtube.com/shorts格式)
- 用户要求总结或转录YouTube视频
- 用户请求获取YouTube视频的内容信息
- 你需要分析视频内容用于调研或内容创作
Dependencies
依赖项
Required: MCP YouTube Transcript server must be installed at:
/root/clawd/mcp-server-youtube-transcriptIf not present, install it:
bash
cd /root/clawd
git clone https://github.com/kimtaeyoon83/mcp-server-youtube-transcript.git
cd mcp-server-youtube-transcript
npm install && npm run build必要依赖: 需在以下路径安装MCP YouTube Transcript服务器:
/root/clawd/mcp-server-youtube-transcript若未安装,请执行以下命令:
bash
cd /root/clawd
git clone https://github.com/kimtaeyoon83/mcp-server-youtube-transcript.git
cd mcp-server-youtube-transcript
npm install && npm run buildWorkflow
工作流程
1. Detect YouTube URL
1. 识别YouTube URL
Extract video ID from these patterns:
https://www.youtube.com/watch?v=VIDEO_IDhttps://youtu.be/VIDEO_IDhttps://www.youtube.com/shorts/VIDEO_ID- Direct video ID: (11 characters)
VIDEO_ID
从以下格式中提取视频ID:
https://www.youtube.com/watch?v=VIDEO_IDhttps://youtu.be/VIDEO_IDhttps://www.youtube.com/shorts/VIDEO_ID- 直接输入视频ID:(11个字符)
VIDEO_ID
2. Fetch Transcript
2. 获取字幕
Run this command to get the transcript:
bash
cd /root/clawd/mcp-server-youtube-transcript && node --input-type=module -e "
import { getSubtitles } from './dist/youtube-fetcher.js';
const result = await getSubtitles({ videoID: 'VIDEO_ID', lang: 'en' });
console.log(JSON.stringify(result, null, 2));
" > /tmp/yt-transcript.jsonReplace with the extracted ID. Read the output from .
VIDEO_ID/tmp/yt-transcript.json执行以下命令获取字幕:
bash
cd /root/clawd/mcp-server-youtube-transcript && node --input-type=module -e "
import { getSubtitles } from './dist/youtube-fetcher.js';
const result = await getSubtitles({ videoID: 'VIDEO_ID', lang: 'en' });
console.log(JSON.stringify(result, null, 2));
" > /tmp/yt-transcript.json将替换为提取到的视频ID,从读取输出结果。
VIDEO_ID/tmp/yt-transcript.json3. Process the Data
3. 数据处理
Parse the JSON to extract:
- - Video title
result.metadata.title - - Channel name
result.metadata.author - - Formatted view count
result.metadata.viewCount - - Publication date
result.metadata.publishDate - - Language used
result.actualLang - - Array of transcript segments
result.lines
Full text:
result.lines.map(l => l.text).join(' ')解析JSON文件提取以下信息:
- - 视频标题
result.metadata.title - - 频道名称
result.metadata.author - - 格式化后的播放量
result.metadata.viewCount - - 发布日期
result.metadata.publishDate - - 使用的语言
result.actualLang - - 字幕片段数组
result.lines
完整文本:
result.lines.map(l => l.text).join(' ')4. Generate Summary
4. 生成摘要
Create a structured summary using this template:
markdown
📹 **Video:** [title]
👤 **Channel:** [author] | 👁️ **Views:** [views] | 📅 **Published:** [date]
**🎯 Main Thesis:**
[1-2 sentence core argument/message]
**💡 Key Insights:**
- [insight 1]
- [insight 2]
- [insight 3]
- [insight 4]
- [insight 5]
**📝 Notable Points:**
- [additional point 1]
- [additional point 2]
**🔑 Takeaway:**
[Practical application or conclusion]Aim for:
- Main thesis: 1-2 sentences maximum
- Key insights: 3-5 bullets, each 1-2 sentences
- Notable points: 2-4 supporting details
- Takeaway: Actionable conclusion
使用以下模板创建结构化摘要:
markdown
📹 **视频:** [标题]
👤 **频道:** [频道名] | 👁️ **播放量:** [播放量] | 📅 **发布日期:** [日期]
**🎯 核心论点:**
[1-2句话概括核心观点/信息]
**💡 关键见解:**
- [见解1]
- [见解2]
- [见解3]
- [见解4]
- [见解5]
**📝 重要细节:**
- [补充细节1]
- [补充细节2]
**🔑 行动建议:**
[可落地的结论或建议]注意事项:
- 核心论点:最多1-2句话
- 关键见解:3-5个要点,每个要点1-2句话
- 重要细节:2-4个支撑性细节
- 行动建议:可落地的结论
5. Save Full Transcript
5. 保存完整字幕
Save the complete transcript to a timestamped file:
/root/clawd/transcripts/YYYY-MM-DD_VIDEO_ID.txtInclude in the file:
- Video metadata header (title, channel, URL, date)
- Full transcript text
- URL reference for easy lookup
将完整字幕保存至带时间戳的文件:
/root/clawd/transcripts/YYYY-MM-DD_VIDEO_ID.txt文件需包含:
- 视频元数据头部(标题、频道、URL、日期)
- 完整字幕文本
- 视频URL(便于快速查看)
6. Platform-Specific Delivery
6. 平台专属交付方式
If channel is Telegram:
bash
message --action send --channel telegram --target CHAT_ID \
--filePath /root/clawd/transcripts/YYYY-MM-DD_VIDEO_ID.txt \
--caption "📄 YouTube Transcript: [title]"If channel is other/webchat:
Just reply with the summary (no file attachment).
若为Telegram频道:
bash
message --action send --channel telegram --target CHAT_ID \
--filePath /root/clawd/transcripts/YYYY-MM-DD_VIDEO_ID.txt \
--caption "📄 YouTube字幕:[标题]"若为其他网页聊天频道:
仅回复摘要内容(无需附加文件)。
7. Reply with Summary
7. 回复用户摘要
Send the structured summary as your response to the user.
将结构化摘要作为回复发送给用户。
Real Case Study
实际案例
User: Content creator researching competitor YouTube strategies
Challenge: Needed to analyze 20+ competitor videos per week to identify trending topics, messaging patterns, and content gaps. Manual process: watch video, take notes, transcribe key quotes. Time: 30-45 min per video.
Solution with youtube-summarizer:
- Drop YouTube URL in chat
- Get structured summary in 20 seconds
- Full transcript saved for reference
- Copy key insights for content planning doc
Workflow example:
User: Analyze this video: https://youtube.com/watch?v=abc123
[20 seconds later]
📹 Video: "10 AI Tools That Will Replace Your Job in 2026"
👤 Channel: TechFuturist | 👁️ Views: 847K | 📅 Published: Jan 12, 2026
🎯 Main Thesis:
AI tools are automating creative and knowledge work faster than expected, but the real opportunity is in augmentation, not replacement.
💡 Key Insights:
- ChatGPT usage among marketers jumped from 12% to 67% in one year
- Video editing time reduced by 80% using AI tools like Descript
- The biggest wins come from combining tools (Notion + Claude + Zapier)
- Companies hiring "AI workflow designers" to optimize human-AI collaboration
- Workers using AI secretly outperform peers by 40% (BCG study)
📝 Notable Points:
- Shows examples of 3 small businesses that 10× output with AI
- Warns against over-automation: "AI can write, but can't think strategically"
🔑 Takeaway:
Don't ask "Will AI replace me?" Ask "How can I use AI to become 10× more valuable?"Results after 8 weeks:
- Time saved: 25 hours/week (from 600 min to 60 min for 20 videos)
- Content output: 3 videos/week (up from 1/week)
- Better insights: Full transcripts searchable, found patterns missed when just watching
- Competitive intel: Built database of 160+ competitor video summaries with key quotes
- ROI quote: "This skill turned competitor research from a chore into an assembly line."
用户: 内容创作者,需调研竞品YouTube策略
挑战: 每周需分析20+竞品视频,识别热门话题、话术模式及内容缺口。手动流程:观看视频、记笔记、转录关键引语。耗时:每视频30-45分钟。
使用YouTube Summarizer后的解决方案:
- 在聊天中粘贴YouTube URL
- 20秒内获取结构化摘要
- 完整字幕自动保存,便于后续查阅
- 复制关键见解用于内容规划文档
工作流示例:
用户:分析这个视频:https://youtube.com/watch?v=abc123
[20秒后]
📹 视频:"2026年将取代你工作的10款AI工具"
👤 频道:TechFuturist | 👁️ 播放量:847K | 📅 发布日期:2026年1月12日
🎯 核心论点:
AI工具正在以超出预期的速度自动化创意与知识工作,但真正的机会在于人机协作而非替代。
💡 关键见解:
- 营销人员中ChatGPT的使用率在一年内从12%飙升至67%
- 使用Descript等AI工具可将视频编辑时间缩短80%
- 最大收益来自工具组合使用(Notion + Claude + Zapier)
- 企业开始招聘「AI工作流设计师」优化人机协作
- 秘密使用AI的员工绩效比同行高出40%(BCG研究)
📝 重要细节:
- 展示了3家借助AI将产出提升10倍的小企业案例
- 警告过度自动化风险:「AI能写作,但无法进行战略思考」
🔑 行动建议:
不要问「AI会取代我吗?」,要问「我如何用AI让自己的价值提升10倍?」8周后的成果:
- 节省时间: 每周节省25小时(20个视频从600分钟降至60分钟)
- 内容产出: 每周3个视频(从每周1个提升)
- 更精准的见解: 完整字幕可搜索,发现了仅观看视频时遗漏的模式
- 竞品情报: 建立了包含160+竞品视频摘要及关键引语的数据库
- ROI评价: 「这个工具把竞品调研从苦差事变成了流水线作业。」
Why This Beats Manual Methods
为何本工具优于手动方法
| Method | Time | Gets Metadata | Structured Output | Searchable Archive | Cloud-Friendly |
|---|---|---|---|---|---|
| Watch + take notes | 30-45 min | No | No | Manual only | N/A |
| YouTube transcript feature | 5 min | No | No | No | Yes |
| yt-dlp | 2-5 min | Yes | No | Yes | ❌ Blocked on VPS |
| Copy to ChatGPT | 10 min | No | Sometimes | No | Yes |
| This skill | 20 sec | Yes | Yes | Yes | ✅ Works on VPS |
| 方法 | 耗时 | 是否获取元数据 | 是否生成结构化输出 | 是否支持可搜索存档 | 是否兼容云环境 |
|---|---|---|---|---|---|
| 观看+记笔记 | 30-45分钟 | 否 | 否 | 仅手动存档 | 不适用 |
| YouTube自带字幕功能 | 5分钟 | 否 | 否 | 否 | 是 |
| yt-dlp | 2-5分钟 | 是 | 否 | 是 | ❌ VPS环境下被封锁 |
| 复制到ChatGPT | 10分钟 | 否 | 有时可以 | 否 | 是 |
| 本工具 | 20秒 | 是 | 是 | 是 | ✅ 支持VPS环境 |
Error Handling
错误处理
If transcript fetch fails:
- Check if video has captions enabled
- Try with fallback if requested language unavailable
lang: 'en' - Inform user that transcript is not available and suggest alternatives:
- Manual YouTube transcript feature (Settings → Show transcript)
- Video may not have captions
- Try a different video
If MCP server not installed:
- Provide installation instructions
- Offer to install it automatically if in appropriate context
If video ID extraction fails:
- Ask user to provide the full YouTube URL or video ID
If video is age-restricted or private:
- Inform user that transcript cannot be accessed due to restrictions
- Suggest checking video privacy settings
若字幕获取失败:
- 检查视频是否启用了字幕
- 若请求的语言不可用,尝试使用作为备选
lang: 'en' - 告知用户无法获取字幕,并提供替代方案:
- 使用YouTube自带的字幕功能(设置→显示字幕)
- 该视频可能未添加字幕
- 尝试其他视频
若MCP服务器未安装:
- 提供安装说明
- 若场景允许,可自动完成安装
若视频ID识别失败:
- 请用户提供完整的YouTube URL或视频ID
若视频为年龄限制或私有视频:
- 告知用户因权限限制无法获取字幕
- 建议用户检查视频隐私设置
Examples
示例
Example 1: Tech Tutorial
示例1:技术教程
Input:
https://youtube.com/watch?v=dQw4w9WgXcQOutput:
markdown
📹 **Video:** "Building a SaaS from Scratch: Lessons from $10K MRR"
👤 **Channel:** IndieHackerTV | 👁️ **Views:** 124K | 📅 **Published:** Feb 1, 2026
**🎯 Main Thesis:**
Most SaaS founders fail because they build for 6 months before talking to customers. The path to $10K MRR is customer conversations first, MVP second.
**💡 Key Insights:**
- Interviewed 50 potential customers before writing a single line of code
- First paid customer signed up with a Figma mockup (no product built yet)
- Charged $99/month from day 1 (no free tier, no discounts)
- Spent $0 on ads; all growth from Twitter + Reddit engagement
- Hit $10K MRR in 9 months by saying "no" to feature requests that didn't fit ICP
**📝 Notable Points:**
- Used Stripe payment links before building a billing system
- First 3 customers came from solving their problem in public on Twitter
- Weekly "build in public" updates on Twitter drove 40% of signups
**🔑 Takeaway:**
Validate demand before building. If 10 people won't pay for a mockup, 1,000 won't pay for the real product.输入:
https://youtube.com/watch?v=dQw4w9WgXcQ输出:
markdown
📹 **视频:** "从零搭建SaaS:月入1万美元的经验教训"
👤 **频道:** IndieHackerTV | 👁️ **播放量:** 124K | 📅 **发布日期:** 2026年2月1日
**🎯 核心论点:**
大多数SaaS创始人失败的原因是先开发6个月产品再接触用户。月入1万美元的正确路径是先做用户调研,再开发MVP。
**💡 关键见解:**
- 写代码前先采访了50位潜在用户
- 仅靠Figma原型就签下了第一个付费客户(产品尚未开发)
- 从第一天起就定价99美元/月(无免费版、无折扣)
- 广告投入为0,所有增长来自Twitter + Reddit互动
- 9个月内达到月入1万美元,秘诀是拒绝不符合目标用户的功能请求
**📝 重要细节:**
- 在构建计费系统前使用Stripe支付链接
- 前3位客户来自Twitter上的公开问题解决
- 每周在Twitter上更新「公开开发进度」,带来了40%的新用户
**🔑 行动建议:**
先验证需求再开发产品。如果10个人都不为原型付费,那1000个人也不会为成品付费。Example 2: Business Strategy Video
示例2:商业策略视频
Input:
https://youtu.be/abc123xyzOutput:
markdown
📹 **Video:** "Why Notion's Business Model is Genius"
👤 **Channel:** SaaS Breakdowns | 👁️ **Views:** 456K | 📅 **Published:** Jan 28, 2026
**🎯 Main Thesis:**
Notion's growth strategy flips traditional SaaS: give away the product for free to individuals, monetize when they bring it to work.
**💡 Key Insights:**
- 80% of Notion's enterprise deals started with a single employee using the free plan
- Bottom-up adoption = zero sales team needed for first $10M ARR
- Templates marketplace created a content flywheel (100K+ free templates)
- Personal use (free) → Team use (paid) conversion rate: 23% (industry avg: 2-5%)
- Community evangelism replaced traditional marketing (4M+ Reddit/Discord members)
**📝 Notable Points:**
- Notion's viral coefficient: 1.4 (every user invites 1.4 others on average)
- Template creators drive 30% of new user acquisition
- Pricing strategy: free until 10 people = no friction to start
**🔑 Takeaway:**
Build a product individuals love first. Enterprise sales will follow when employees demand it at work.输入:
https://youtu.be/abc123xyz输出:
markdown
📹 **视频:** "为何Notion的商业模式如此出色"
👤 **频道:** SaaS Breakdowns | 👁️ **播放量:** 456K | 📅 **发布日期:** 2026年1月28日
**🎯 核心论点:**
Notion的增长策略颠覆了传统SaaS模式:向个人免费提供产品,当用户将其引入职场时再进行变现。
**💡 关键见解:**
- Notion 80%的企业客户始于单个员工使用免费版
- 自下而上的采用方式:首个1000万美元ARR无需销售团队
- 模板市场形成了内容飞轮(10万+免费模板)
- 个人版(免费)→团队版(付费)转化率:23%(行业平均2-5%)
- 社区传播取代了传统营销(400万+ Reddit/Discord成员)
**📝 重要细节:**
- Notion的病毒系数:1.4(每位用户平均邀请1.4位新用户)
- 模板创作者带来了30%的新用户
- 定价策略:10人以内免费→无使用门槛
**🔑 行动建议:**
先打造个人用户喜爱的产品。当员工在工作中主动要求使用时,企业订单自然会来。Quality Guidelines
质量规范
- Be concise: Summary should be scannable in 30 seconds
- Be accurate: Don't add information not in the transcript
- Be structured: Use consistent formatting for easy reading
- Be contextual: Adjust detail level based on video length
- Short videos (<5 min): Brief summary (3 key insights)
- Medium videos (5-30 min): Standard format (5 key insights)
- Long videos (>30 min): Detailed breakdown (7+ insights, split into sections if needed)
- Extract value: Focus on actionable insights, data points, and contrarian takes (not generic advice)
- 简洁性: 摘要需在30秒内可快速浏览
- 准确性: 不得添加字幕中没有的信息
- 结构化: 使用统一格式提升可读性
- 适配性: 根据视频长度调整细节程度
- 短视频(<5分钟):简洁摘要(3个关键见解)
- 中长视频(5-30分钟):标准格式(5个关键见解)
- 长视频(>30分钟):详细分解(7+个见解,必要时分章节)
- 价值导向: 聚焦可落地的见解、数据点及反常识观点(而非通用建议)
Pro Tips
实用技巧
For Better Summaries:
- Prioritize data points - Numbers, percentages, study citations stand out
- Extract quotes - Memorable one-liners make summaries shareable
- Identify frameworks - If video presents a method/process, extract the steps
- Spot contrarian takes - Unconventional wisdom is more valuable than common advice
- Note proof - Examples, case studies, before/after results add credibility
For Research Workflows:
- Build a transcript library - Organize by topic/niche for pattern spotting
- Search across transcripts - Use or text search to find mentions of specific topics
grep - Track trends - Same topic across multiple videos = rising trend
- Extract prompts - Save useful frameworks/methods as reusable prompts
For Content Creation:
- Find content gaps - What questions are asked but not fully answered?
- Analyze top performers - What structure/pacing do high-view videos use?
- Extract hooks - First 30 seconds of transcript = proven hook patterns
- Repurpose insights - Turn video insights into Twitter threads, blog posts, newsletters
提升摘要质量:
- 优先提取数据 - 数字、百分比、研究引用更引人注目
- 提取关键引语 - 易记的金句让摘要更具传播性
- 识别框架模型 - 若视频介绍了方法/流程,提取关键步骤
- 捕捉反常识观点 - 非传统智慧比通用建议更有价值
- 记录案例支撑 - 示例、案例研究、前后对比结果可提升可信度
调研工作流优化:
- 构建字幕库 - 按主题/细分领域分类,便于发现模式
- 跨字幕搜索 - 使用或文本搜索查找特定主题的提及内容
grep - 追踪趋势 - 多个视频涉及同一主题→上升趋势
- 保存可复用提示词 - 将有用的框架/方法保存为可复用的提示词
内容创作优化:
- 发现内容缺口 - 哪些问题被提出但未被充分解答?
- 分析高播放量视频 - 高播放量视频采用了何种结构/节奏?
- 提取钩子模板 - 字幕的前30秒=经过验证的钩子模式
- 复用见解 - 将视频见解转化为Twitter线程、博客文章、新闻通讯
Configuration
配置选项
Standard Mode (default)
标准模式(默认)
youtube-summarizer [URL]- Fetches transcript in English
- Generates structured summary
- Saves transcript to file
- Sends to messaging platform if applicable
youtube-summarizer [URL]- 获取英文字幕
- 生成结构化摘要
- 将字幕保存至文件
- 若适用,发送至消息平台
Quick Mode
快速模式
youtube-summarizer [URL] --quick- Thesis + 3 key insights only
- No transcript file saved
- Faster processing for rapid research
youtube-summarizer [URL] --quick- 仅包含核心论点+3个关键见解
- 不保存字幕文件
- 处理速度更快,适用于快速调研
Deep Dive Mode
深度分析模式
youtube-summarizer [URL] --deep- Extended summary with timestamps
- Section-by-section breakdown for long videos
- Includes all notable quotes
youtube-summarizer [URL] --deep- 包含时间戳的扩展摘要
- 长视频按逻辑章节分解
- 包含所有重要引语
Language-Specific
指定语言模式
youtube-summarizer [URL] --lang es- Fetches transcript in specified language
- Falls back to English if unavailable
youtube-summarizer [URL] --lang es- 获取指定语言的字幕
- 若指定语言不可用,自动 fallback 到英文
Installation & Setup
安装与设置
bash
undefinedbash
undefined1. Clone and install MCP server
1. 克隆并安装MCP服务器
cd /root/clawd
git clone https://github.com/kimtaeyoon83/mcp-server-youtube-transcript.git
cd mcp-server-youtube-transcript
npm install && npm run build
cd /root/clawd
git clone https://github.com/kimtaeyoon83/mcp-server-youtube-transcript.git
cd mcp-server-youtube-transcript
npm install && npm run build
2. Test installation
2. 测试安装
node --input-type=module -e "
import { getSubtitles } from './dist/youtube-fetcher.js';
const result = await getSubtitles({ videoID: 'dQw4w9WgXcQ', lang: 'en' });
console.log(result.metadata.title);
"
node --input-type=module -e "
import { getSubtitles } from './dist/youtube-fetcher.js';
const result = await getSubtitles({ videoID: 'dQw4w9WgXcQ', lang: 'en' });
console.log(result.metadata.title);
"
3. Create transcripts directory
3. 创建字幕存储目录
mkdir -p /root/clawd/transcripts
mkdir -p /root/clawd/transcripts
4. Verify skill is ready
4. 验证工具是否就绪
youtube-summarizer --check-setup
undefinedyoutube-summarizer --check-setup
undefinedCommon Issues
常见问题
Issue: "Transcript not available"
- Cause: Video has no captions/subtitles enabled
- Fix: Ask video creator to enable captions, or try a different video
Issue: "Failed to fetch transcript" (on VPS)
- Cause: YouTube may have updated their API
- Fix: Update MCP server:
cd /root/clawd/mcp-server-youtube-transcript && git pull && npm install && npm run build
Issue: "Video ID not recognized"
- Cause: Malformed URL or unsupported format
- Fix: Copy URL directly from YouTube address bar
问题: "无法获取字幕"
- 原因: 视频未启用字幕/字幕功能
- 解决方法: 请视频创作者启用字幕,或尝试其他视频
问题: "获取字幕失败"(VPS环境下)
- 原因: YouTube可能更新了API
- 解决方法: 更新MCP服务器:
cd /root/clawd/mcp-server-youtube-transcript && git pull && npm install && npm run build
问题: "视频ID无法识别"
- 原因: URL格式错误或不支持
- 解决方法: 直接从YouTube地址栏复制URL
Future Enhancements (Roadmap)
未来规划(路线图)
- Multi-video batch processing (analyze playlists)
- Sentiment analysis on transcript (positive/negative/neutral tone)
- Speaker diarization (identify different speakers in interviews/panels)
- Automatic chapter detection (split long videos into logical sections)
- Cross-video pattern analysis (find common themes across multiple videos)
- 多视频批量处理(支持播放列表分析)
- 字幕情感分析(积极/消极/中性语气)
- 说话人分离(识别访谈/圆桌会议中的不同说话人)
- 自动章节识别(将长视频划分为逻辑章节)
- 跨视频模式分析(发现多个视频中的共同主题)
Support
支持与反馈
Issues or suggestions? Provide:
- YouTube URL that failed
- Error message (if any)
- Expected vs actual behavior
- MCP server version:
cd /root/clawd/mcp-server-youtube-transcript && git rev-parse HEAD
Built on MCP YouTube Transcript server (Android emulation for cloud reliability).
Turn any YouTube video into structured, searchable knowledge in 20 seconds.
遇到问题或有建议?请提供以下信息:
- 失败的YouTube URL
- 错误信息(若有)
- 预期结果与实际结果对比
- MCP服务器版本:
cd /root/clawd/mcp-server-youtube-transcript && git rev-parse HEAD
基于MCP YouTube Transcript服务器构建(通过安卓模拟实现云环境可靠性)。
20秒内将任意YouTube视频转换为结构化、可搜索的知识内容。