youtube-niche-finder
Self-hosted YouTube niche & outlier-video research tool (NexLev/vidIQ alternative). Runs on free YouTube Data API v3 + local PostgreSQL. Provides viral video discovery, channel tracking, and trend analysis without paid subscriptions.
Ficha actualizada 22 sept 2026, 20:54 · upstream 22 sept 2026, 20:52 · release v0.1.0
Qué es youtube-niche-finder
Descripción editorial construida a partir del repositorio, su documentación y sus señales de mantenimiento.
This project is a self-hosted alternative to popular tools like NexLev and vidIQ for discovering viral videos and outlier channels within specific niches. It leverages the free YouTube Data API v3 combined with a local PostgreSQL database to provide comprehensive analytics including view velocity, subscriber growth rates, trending categories, keywords, and best publishing times. The tool is built in three components: an MCP server for Claude Desktop integration, an HTTP API for web dashboards, and a background worker that logs historical data without requiring paid subscriptions or LLM keys on the server side. A separate Chrome extension provides similar outlier scoring directly within YouTube's interface.
- Discover viral videos in your niche by analyzing small channels that overperform expectations
- Identify outlier channels with superior performance metrics compared to their peers
- Track specific channels for growth patterns and subscriber acquisition velocity
- Monitor trending categories and keywords within a given time period (24h, 48h, weekly, monthly)
- Find the optimal publishing times based on historical engagement data
- Build comprehensive niche intelligence by aggregating multiple metrics across thousands of channels
- Runs entirely on free YouTube Data API v3 with no paid subscriptions required
- No LLM key needed on the server side — semantic classification is handled client-side via Claude Desktop MCP tools
- Single shared codebase between dashboard and Claude Desktop, ensuring identical calculations
- Zero-build ES-modules frontend that runs without npm or build step dependencies
- Provides outlier scores, view velocity, and growth metrics directly on YouTube channel pages
- YouTube API rate limits apply — requires quota management for high-volume use cases
- No real-time data available; all historical data is stored locally in PostgreSQL
- Chrome extension only works within the same browser instance (no cross-browser sync)
- Channel RSS feed parsing may not cover all video content on a channel
- Trending keyword detection relies on YouTube's algorithm and may lag behind real-time trends
Perfil de infraestructura
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Deploy with Docker Compose: run `docker compose up -d web worker` to start the PostgreSQL database, background worker for data processing, and HTTP API service. The MCP server is launched separately via `scripts/mcp-docker.sh`. For local development without Docker, use `make dev` or `make local-run` which sets up a Python virtual environment with backend dependencies. Always set `NICHE_DATABASE_URL=postgresql://niches:niches@localhost:5433/niches` in `.env` — this is the host-level connection string that overrides container defaults to avoid port conflicts between services.
Stack y dependencias
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