MCP YouTube Transcript
An MCP server retrieving transcripts of YouTube videos
Description from the maker (original English)
Universal web content extraction — any URL to LLM-ready markdown. HTML, YouTube, PDF, DOCX.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"markgrab": {
"command": "uvx",
"args": [
"markgrab"
]
}
}
}Run this in your terminal
claude mcp add markgrab -- uvx markgrabPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"markgrab": {
"command": "uvx",
"args": [
"markgrab"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"markgrab": {
"type": "stdio",
"command": "uvx",
"args": [
"markgrab"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The publisher (ArkNill) is not the repo owner (QuartzUnit); someone else may have listed it
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 0 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.2) reached the registry 8 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
An MCP server retrieving transcripts of YouTube videos
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
한국어 문서 · llms.txt
Universal web content extraction — any URL to LLM-ready markdown.
from markgrab import extract
result = await extract("https://example.com/article") print(result.markdown) # clean markdown print(result.title) # "Article Title" print(result.word_count) # 1234 print(result.language) # "en"
pip install markgrab
Optional extras for specific content types:
pip install "markgrab[browser]" # Playwright for JS-rendered pages
pip install "markgrab[youtube]" # YouTube transcript extraction pip install "markgrab[pdf]" # PDF text extraction pip install "markgrab[docx]" # DOCX text extraction pip install "markgrab[all]" # everything
import asyncio
from markgrab import extract
async def main():
result = await extract("https://example.com/article")
result = await extract("https://youtube.com/watch?v=dQw4w9WgXcQ")
result = await extract("https://arxiv.org/pdf/1706.03762")
result = await extract( "https://example.com", max_chars=30_000, # limit output length (default: 50K) use_browser=True, # force Playwright rendering stealth=True, # anti-bot stealth scripts (opt-in) timeout=60.0, # request timeout in seconds proxy="http://proxy:8080", )
asyncio.run(main())
markgrab https://example.com # markdown output
markgrab https://example.com -f text # plain text markgrab https://example.com -f json # structured JSON markgrab https://example.com --browser # force browser rendering markgrab https://example.com --max-chars 10000 # limit output
result.title # page title
result.text # plain text result.markdown # LLM-ready markdown result.word_count # word count result.language # detected language ("en", "ko", ...) result.content_type # "article", "video", "pdf", "docx" result.source_url # final URL (after redirects) result.metadata # extra metadata (video_id, page_count, etc.)
flowchart TD
A["🔗 URL Input"] --> B{"Content\nType?"} B -->|"HTML"| C["HTTP fetch\n(httpx)"] C --> D{"JS\nrequired?"} D -->|"no"| E["HTML Parser\n→ clean markdown"] D -->|"yes"| F["Playwright\nfallback"] F --> E B -->|"YouTube"| G["Transcript API\n→ timestamped markdown"] B -->|"PDF"| H["PDF Parser\n→ structured markdown"] B -->|"DOCX"| I["DOCX Parser\n→ markdown"] E --> J["✅ LLM-ready\nMarkdown"] G --> J H --> J I --> J
For HTML pages, if the initial httpx fetch yields fewer than 50 words, MarkGrab automatically retries with Playwright to handle JavaScript-rendered content.
This software is provided for legitimate purposes only. By using MarkGrab, you agree to the following:
robots.txt. Users are solely responsible for checking and respecting robots.txt directives and the terms of service of any website they access.youtube-transcript-api library, which uses YouTube's internal (unofficial) caption API. This may not comply with YouTube's Terms of Service. Use at your own discretion and risk.stealth=True feature modifies browser fingerprinting signals to reduce bot detection. This feature is intended for legitimate use cases such as testing, research, and accessing content that is publicly available to regular browser users. Users are responsible for ensuring their use complies with applicable laws and the terms of service of target websites.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND. See the LICENSE file for the full MIT license text.
MarkGrab builds on excellent open-source work and well-established techniques:
anti_bot/stealth.py modulearticle > main > body) and link density filtering concepts used in the density filterBuilt with httpx, BeautifulSoup, markdownify, Playwright, youtube-transcript-api, pdfplumber, and python-docx.
MIT
Part of the QuartzUnit ecosystem — composable Python libraries for data collection, extraction, search, and AI agent safety.