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Hey r/selfhosted!

The price for vidIQ, 1of10 and similar tools is too high and I tried to find a better way to let AI do research on YouTube. So I build the MCP - kirbah/mcp-youtube. It is more than just a wrapper on top of existing YouTube APIs.

The recent improvements are CreatorLens skill as an extra layer of best practices from YouTube growth strategiest, that turns raw YouTube data into an actual diagnosis not just numbers.

This is an year old project and since I have not posted about it earlier here are key features:

• Audits your channel and competitors using findConsistentOutlierChannels to spot channels that consistently outperform in your niche. This is most heavy feature that search top performing videos, checks corresponding channels performance and return just few channels that pass all checks.
• Pulls channel stats, top videos, trending videos.
• Fetches transcripts for content analysis, and comments for sentiment feedback
• Caches everything in MongoDB so repeated research does not burn your daily API quota.

Key design decisions:

• use YouTube Data API instead scrappers
• keep only minimal data returned from MCP with options to get partial data
• minimize number of tools. Only really needed like video description, stats and transcripts retrieval

Setup: create free YouTube Data API key, and a MongoDB instance for caching. I use a free MongoDB Atlas cluster since it is easier. it just cache YouTube data, nothing sensitive. And make easier to do compex searches not supported in YouTube API.

Limitations: you have to create free YouTube API key and create free mongodb at Atlas cluster.

Repo: https://github.com/kirbah/mcp-youtube

Would love to get feedback.