YouTube Research MCP

🇰🇷 한국어

"The real insight in a YouTube video lives in the comments."

An MCP server that turns YouTube into a multi-dimensional research source for your AI assistant.

Cross-reference what creators say (transcripts) with what viewers actually think (comments), and run complex multi-video research — all handled directly by your AI. Core features work without an API key. Comment analysis requires a YouTube Data API key.

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What can you do with this?

• Compare multiple videos — Collect transcripts from several videos on the same topic and find common claims, contradictions, and patterns
• Analyze audience sentiment ⚠️ API key required — Pull comments alongside transcripts to compare "what creators say" vs "what viewers actually think"
• Track channel trends — Analyze a channel's recent videos to see what topics they're focusing on
• Summarize any video — Give your AI a URL and get the key points extracted immediately

YouTube as a reading research source, not a watching platform.

✨ See what's possible

👤 You type (with API key):

"Summarize the pros and cons from this review video, and tell me the top 3 complaints that keep coming up in the comments."

🤖 AI responds:

"The creator highlighted camera performance and battery life as key strengths. However, analyzing the collected comments, the most frequently mentioned complaints from actual users were: ① overheating issues, ② frame drops in certain apps, and ③ slow charging speed. There's a noticeable gap between the creator's positive take and real-world user experience."

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Feature Overview

Feature	Without API key	With API key
Video transcript collection	✅	✅
Video metadata lookup	✅ (via yt-dlp)	✅
Channel video analysis	✅ (via yt-dlp)	✅
Keyword search	❌	✅
Comment collection & sentiment analysis	❌	✅
API quota monitoring	❌	✅

Comment-based sentiment analysis requires a YouTube Data API key. Getting a key is free — you receive 10,000 units per day.

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Design Principles

• No LLM calls — This server only collects and structures data. All analysis and synthesis is done by your AI assistant.
• Prompt injection defense — All transcript and comment content is tagged with a safety_notice to mark it as untrusted external content.
• No surprise API bills — Results are cached in SQLite to block redundant API calls. Re-analyzing the same video costs zero additional quota.
• Works without an API key — Core transcript and channel analysis runs via yt-dlp, no Google account needed.

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See it in action

After setup, just type naturally in your AI chat:

Without an API key — ready immediately

Summarize this video: https://www.youtube.com/watch?v=tTw1z10yMCI

Analyze the last 5 videos from @fireship and tell me what tech topics they've been covering lately

Compare these 3 videos — what does each one argue, and where do they agree or disagree?
https://www.youtube.com/watch?v=aaa
https://www.youtube.com/watch?v=bbb
https://www.youtube.com/watch?v=ccc

With an API key — comment sentiment included

Search for 4 videos about "AI agents", compare their main arguments,
and summarize the recurring reactions in the comments

Compare the content and comment reactions from these two videos —
do viewers agree with the creators or push back?
https://www.youtube.com/watch?v=aaa
https://www.youtube.com/watch?v=bbb

Find 3 videos on "Python vs JavaScript 2025" and summarize:
what creators agree on, where they differ, and what viewers keep saying in the comments

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Installation

Recommended — zero install with uvx

No cloning or virtual environments needed. Install uv (a fast Python package manager), and then configure your MCP client directly.

# Install uv (if you don't have it yet)
curl -LsSf https://astral.sh/uv/install.sh | sh   # macOS / Linux
# or: winget install astral-sh.uv                  # Windows

That's it for installation. Head straight to the Connecting to Your MCP Client section below.

Alternative — install via pip

pip install youtube-research-mcp

For developers — clone and run from source

git clone https://github.com/lee-s-dev/youtube-research-mcp
cd youtube-research-mcp
pip install -e .

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Connecting to Your MCP Client

The examples below use Claude Desktop. Any MCP-compatible client can be configured the same way.

Open ~/Library/Application Support/Claude/claude_desktop_config.json and add the following.

If the file doesn't exist, create it. The Claude Desktop app must be run at least once for this directory to appear.

Without API key — transcripts + channel analysis

{
  "mcpServers": {
    "youtube-research": {
      "command": "uvx",
      "args": ["youtube-research-mcp"]
    }
  }
}

With API key — all features enabled

{
  "mcpServers": {
    "youtube-research": {
      "command": "uvx",
      "args": ["youtube-research-mcp"],
      "env": {
        "YOUTUBE_API_KEY": "AIzaSy..."
      }
    }
  }
}

After saving, fully quit and restart your MCP client for changes to take effect.

If you installed via pip instead of uvx, replace "command": "uvx" and "args": ["youtube-research-mcp"] with "command": "youtube-research-mcp" and "args": [].

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Getting a YouTube API Key (Optional)

Required for search and comment features. It's free — you get 10,000 units per day, which comfortably covers typical personal use.

Step-by-step

1. Go to Google Cloud Console (requires a Google account)
2. Click the project selector at the top → New Project → name it and create
3. In the left menu: APIs & Services → Library
4. Search YouTube Data API v3 → click Enable
5. APIs & Services → Credentials
6. Click + Create Credentials → API key
7. Copy the generated key

Recommended: Restrict the key

To prevent misuse if the key is ever exposed:

• Click Edit API key
• Under API restrictions, select Restrict key
• Check YouTube Data API v3 → Save

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Tools Reference

No API key required

get_transcript — Fetch a video's transcript

Summarize the key points from this video:
https://www.youtube.com/watch?v=tTw1z10yMCI

Parameter	Description	Default
url_or_video_id	YouTube URL or video ID	Required
languages	Preferred subtitle languages (e.g. ["en", "ko"])	Auto-detect

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analyze_videos — Analyze multiple videos at once

Collects transcripts and metadata in parallel. Adds comments if an API key is configured.

Analyze these 3 videos and compare their arguments — what do they agree on and where do they differ?
https://www.youtube.com/watch?v=aaa
https://www.youtube.com/watch?v=bbb
https://www.youtube.com/watch?v=ccc

Parameter	Description	Default
urls_or_video_ids	List of YouTube URLs or video IDs	Required
languages	Preferred subtitle languages	Auto-detect
include_comments	Include comments (⚠️ API key required)	true
max_comments_per_video	Max comments per video	25
max_transcript_chars	Transcript character limit (0 = no limit)	0

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analyze_channel — Analyze a channel's recent videos

Look at the last 5 videos from @ycombinator and summarize what startup topics they're covering lately

Parameter	Description	Default
channel_id_or_handle	Channel handle or ID	Required
max_videos	Number of videos to collect (max 8)	5
min_duration_seconds	Minimum video length in seconds	120
max_duration_seconds	Maximum video length in seconds	7200
include_comments	Include comments (⚠️ API key required)	true
exclude_shorts	Skip YouTube Shorts	true

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get_capabilities — Check what's available

What tools do I have available right now?

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Requires API key

search_videos — Search YouTube by keyword

Search for 5 recent videos about "AI agents" and give me a summary of each

Parameter	Description	Default
query	Search query	Required
max_results	Maximum number of results	5
published_after	Only videos after this date (YYYY-MM-DD)	None
published_before	Only videos before this date (YYYY-MM-DD)	None
exclude_shorts	Skip YouTube Shorts	false

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get_video_comments — Fetch comments for a video

Parameter	Description	Default
url_or_video_id	YouTube URL or video ID	Required
max_comments	Maximum number of comments	50
order	Sort order (relevance or time)	relevance
include_replies	Include comment replies	false

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collect_video_discussion — Transcript + comments together

Great for comparing what a creator claims with how the audience actually responds.

Fetch the transcript and comments for this video, then compare the creator's claims with viewer reactions:
https://www.youtube.com/watch?v=tTw1z10yMCI

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collect_research_sources — Search → bulk transcript collection

Search for 5 videos comparing "Rust vs Go" and summarize the conclusion each one reaches

Parameter	Description	Default
query	Search query	Required
max_videos	Max videos to process (up to 8)	5
min_duration_seconds	Minimum video length	120
exclude_shorts	Skip Shorts	true
min_view_count	Minimum view count filter	0

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collect_research_discussions — Search → transcripts + comments together

The most powerful research tool. Searches for videos, then collects transcripts and comments for each in parallel.

Search for 3 videos on "LLM fine-tuning techniques", then:
- What do creators commonly emphasize?
- Where do they disagree?
- What questions keep coming up in the comments?

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get_quota_usage — Check today's API usage

Returns how many YouTube API units you've used today and how many remain.

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Example Prompts

Quick single-video summary

Grab the transcript for this video and list the key implementation steps as a numbered list:
https://www.youtube.com/watch?v=tTw1z10yMCI

Multi-video topic comparison

Search for 3 "MCP tutorial" videos and compare:
- How each one explains the setup process
- Common warnings or gotchas they all mention
- Any conflicting advice between them

Audience sentiment analysis (API key required)

Get the transcripts and comments for these two videos and compare:
- What claims get positive reactions vs pushback in the comments?
- Do viewers agree more with one creator over the other?
https://www.youtube.com/watch?v=aaa
https://www.youtube.com/watch?v=bbb

Channel trend report

Analyze the last 5 videos from @fireship and give me a breakdown of:
- What technologies they're focusing on right now
- The general tone (hype, critical, educational)
- Any recurring themes across videos

Product review aggregation (API key required)

Search for 5 "iPhone 16 Pro review" videos and create a comparison table
rating camera, battery, and performance based on what each reviewer says —
then summarize what viewers agree or disagree with in the comments

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How Caching Works

Results are cached in a local SQLite database. Re-analyzing the same video costs zero additional API quota.

Data	Cache duration
Transcripts	30 days
Comments	6 hours
Search results	2 hours
Video metadata	Permanent

Cache location (auto-selected by OS, configurable via YOUTUBE_RESEARCH_CACHE_DB env var):

• macOS: ~/Library/Application Support/youtube-research-mcp/cache.db
• Windows: %APPDATA%\youtube-research-mcp\cache.db
• Linux: ~/.local/share/youtube-research-mcp/cache.db

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Running Tests

# Unit tests (no API key needed)
python -m unittest discover -s tests

# Full suite including live smoke tests (API key required)
YOUTUBE_API_KEY=AIza... python -m unittest discover -s tests

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License

MIT