MEGA → Telegram Leech Bot

Downloads a MEGA folder and uploads every file to all Telegram groups and channels the bot has been added to. Built to run on a Hetzner VPS via Docker.

What it does

• Auto-tracks destinations. Add the bot to a group, or make it an admin in a channel, and it remembers that chat. Remove it and it stops dumping there. No hardcoded chat list.
• Uploads once, fans out by file id. A file is uploaded a single time and then copied to every other chat without re-uploading, so you pay upload bandwidth only once.
• Handles big files. Anything over ~2 GB is split into parts automatically (Telegram's bot upload limit).
• Streams one file at a time. It never needs disk for the whole folder — only for the largest single file — so a 400 GB folder needs the same small volume as a tiny one.
• Resumes after restarts. Progress is saved in SQLite; if the container restarts mid-job, the bot continues from the next unfinished file.
• Owner-only. Only your Telegram user id can issue commands.

You will need

Value	Where to get it
API_ID, API_HASH	https://my.telegram.org → API development tools
BOT_TOKEN	@BotFather → /newbot
OWNER_ID	@userinfobot (your numeric id)
MEGA_EMAIL, MEGA_PASSWORD	your MEGA account (Pro / Pro Lite recommended)

Commands (owner only)

Command	Action
/leech <mega folder url>	download the folder and dump every file
/chats	list the chats it will dump to
/probe <mega folder url>	print the raw MEGA listing (debug)
/cancel	stop after the current file
/start, /help	show help

Deploy on a Hetzner VPS

1. SSH into your Hetzner VPS and install Docker (curl -fsSL https://get.docker.com | sh) if it isn't already installed.
2. Clone this repository onto the VPS:

   git clone <this-repo-url>
   cd mega-leech-bot

3. Copy .env.example to .env and fill in your real values:

   cp .env.example .env

   Set DATA_DIR=/data — this path is inside the container and gets mapped to a persistent folder on the VPS in the next step.
4. Create a folder on the VPS for persistent storage and build the image:

   mkdir -p /opt/mega-leech-bot/data
   docker build -t mega-leech-bot .

   • Size the disk to your largest single file + ~4 GB (e.g. 20 GB is plenty unless you have very large individual files).
5. Run the container, mounting the data folder and restarting automatically on reboot or crash:

   docker run -d --name mega-leech-bot \
     --env-file .env \
     -v /opt/mega-leech-bot/data:/data \
     --restart unless-stopped \
     mega-leech-bot

6. Watch the logs with docker logs -f mega-leech-bot. The one step that occasionally needs a tweak is the MEGAcmd download in the Dockerfile (see the comment there). When the logs show Bot @yourbot started., message your bot /start.

To ship a code update later: git pull, docker build -t mega-leech-bot ., then docker rm -f mega-leech-bot and re-run the docker run command above.

First run — validate small

Before a big folder, test with a small public folder (2–3 files):

1. Add the bot to one test channel as an admin, send /chats to confirm it shows up.
2. Send /leech <small folder url>.
   • If it says "No files found", send /probe <same url> and share the output — the listing parser in mega_client.py can be matched to it.
3. Once a small folder works end to end, run your real one.

Run locally (optional)

pip install -r requirements.txt          # plus install MEGAcmd for your OS
cp .env.example .env                      # then edit .env with real values
python bot.py

Cost note

A Hetzner VPS is billed at a flat monthly rate rather than metered egress, so a leech run's bandwidth doesn't add extra cost the way it would on a pay-per-GB host — just make sure the VPS plan's included traffic covers the folder sizes you expect to dump.

Files

File	Purpose
bot.py	handlers, auto-track, the leech pipeline, startup
mega_client.py	MEGAcmd wrapper (login / list / download)
db.py	SQLite: tracked chats + resume state
utils.py	sizes, progress throttle, file splitter
config.py	loads settings from environment variables
Dockerfile	installs MEGAcmd + Python deps