MCP server to ingest and search study materials using semantic search
A Model Context Protocol (MCP) server that turns video transcripts and study materials into a searchable, AI-powered knowledge base — directly inside Claude Desktop.
Paste a video transcript or point to a PDF, slide deck, DOCX, or image and instantly:
- 🎬 Ingest video transcripts — paste raw text or load .srt/.vtt caption files; timestamps are preserved so you can jump back to the exact moment in the video - 🔍 Search semantically — ask questions in natural language across all your materials, powered by local embeddings (no API cost) - 🎯 Generate quizzes — sample representative context from any material so Claude can quiz you on it - 🧠 Summarize & create flashcards — saved directly to Notion - 📊 Track your library — list materials, inspect overviews, view stats, delete what you no longer need
Everything runs locally by default (ChromaDB + HuggingFace embeddings). Set a single environment variable to switch to pgvector on Supabase/Postgres.
Layer Technology ------ Language Python 3.13 MCP server MCP Python SDK (FastMCP) Embeddings sentence-transformers + HuggingFace models (local inference, PyTorch) Vector stores ChromaDB (local) · pgvector on Supabase/Postgres (cloud) Document parsing Docling (PDF, DOCX, PPTX, HTML, images) + native SRT/VTT parser Integrations Notion API (notion-client) Configuration pydantic-settings (typed, env-based) Tooling Poetry · pytest (+coverage) · ruff · mypy --strict · pre-commit · commitizen CI GitHub Actions (lint, type check, tests on every push/PR)
From the project README.
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