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cast2md

Turn podcast RSS feeds into a searchable, LLM-ready transcript library. Automatically fetches existing transcripts from publishers and Pocket Casts, or transcribes locally with Whisper. Search across everything, or chat with your podcasts via MCP.

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Features

  • RSS Feed Management

    Add podcast feeds via RSS or Apple Podcasts URLs. Automatic episode discovery and polling.

  • Chat with Your Podcasts

    Ask questions, summarize episodes, and explore topics across your library. Claude integration via Model Context Protocol.

  • Hybrid Search

    Full-text and semantic search across episode metadata and transcript content with pgvector.

  • Transcript-First Workflow

    Fetches transcripts from Podcasting 2.0 tags and Pocket Casts before downloading audio for Whisper.

  • Whisper Transcription

    Local transcription with faster-whisper or mlx-whisper. Supports CPU, CUDA, and Apple Silicon.

  • Distributed Transcription

    Use remote machines (M4 Macs, GPU PCs, RunPod) to transcribe in parallel.

  • REST API

    Full API for automation and integration with other tools.

Quick Start

git clone https://github.com/meltforce/cast2md.git
cd cast2md
cp .env.example .env
# Edit .env -- set POSTGRES_PASSWORD at minimum
docker compose up -d

Open http://localhost:8000 to access the web UI.

curl -LsSf https://astral.sh/uv/install.sh | sh
git clone https://github.com/meltforce/cast2md.git
cd cast2md
uv sync --frozen
cp .env.example .env
# Edit .env with your settings
uv run cast2md init-db
uv run cast2md serve

See the Installation Guide for full details.

Personal Project

This is a personal project under active development. I'm sharing it in case others find it useful, but I'm not currently providing support or reviewing pull requests.

Documentation

Section Description
Getting Started What cast2md does and how it works
Installation Docker, manual install, and node setup
Configuration Environment variables and settings
Usage Search and feed management
Administration Status monitoring, settings, queue, CLI, API, and MCP
Features Architecture, transcript sources, search, episode states
Distributed Transcription Multi-machine setup and RunPod GPU workers
Deployment Production deployment and server sizing
Development Dev setup, testing, and UI guidelines