MCP server
by kazuph
Retrieve and transcribe YouTube transcripts with natural language queries. Easily get YouTube transcript or convert YouT
Downloads YouTube video transcripts and metadata so you can ask natural language questions about video content. Supports multiple languages including Japanese, English, Korean, Chinese, and French.
YouTube Subtitles is a community-built MCP server published by kazuph that provides AI assistants with tools and capabilities via the Model Context Protocol. Retrieve and transcribe YouTube transcripts with natural language queries. Easily get YouTube transcript or convert YouT It is categorized under search web, other. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.
You can install YouTube Subtitles in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
YouTube Subtitles is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
README content is unavailable from source data for this server.
Open GitHub repository →Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
Share your MCP server with the developer community
YouTube Subtitles has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired YouTube Subtitles into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We evaluated YouTube Subtitles against two servers with overlapping tools; this profile had the clearer scope statement.
YouTube Subtitles is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, YouTube Subtitles benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: YouTube Subtitles surfaces stars and publisher context so we could sanity-check maintenance before adopting.
YouTube Subtitles reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Useful MCP listing: YouTube Subtitles is the kind of server we cite when onboarding engineers to host + tool permissions.
YouTube Subtitles is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
YouTube Subtitles reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ Use when
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid when
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.