GTS Federator

A powerful RSS-based discovery engine to populate GoToSocial instances.

🏰 Website · 📰 Zeitfresser Matrix Community · 🐘 Fediverse · 💬 Supportchat

✨ Introduction

GTS-Federator is a high-efficiency content discovery tool designed for GoToSocial instances. It solves the "empty timeline" problem of small or personal instances by automatically discovering and federating content from RSS feeds across the Fediverse.

By leveraging RSS feeds from larger instances or specific hashtags, GTS-Federator acts as a lightweight alternative to traditional relays, giving you full control over what kind of content populates your federated timeline.

🏛 Evolution & Credits

GTS-Federator is a refined and modernized fork built upon the innovative concepts of the original Fediverse discovery tools. This project stands on the shoulders of:

• @aliceif – The original creator of HolMirDas, who pioneered the concept of RSS-based federation.
• Matthias – Whose fork introduced essential GoToSocial adaptations and performance improvements.

This version takes these foundations and optimizes them for modern production environments, focusing on native Docker integration, long-term stability, and GoToSocial's unique architectural requirements.

🛠 What this bot is for

GTS-Federator is not a relay in the traditional sense. It is a targeted discovery engine. Instead of receiving everything from a relay, you "pull" exactly what interests you.

It is a perfect fit if you:

• run a personal or small GoToSocial instance (especially on low-power hardware like a Synology NAS or Raspberry Pi)
• want to populate your federated timeline with specific topics (via Hashtag-RSS)
• prefer a pull-based discovery over the "firehose" of public relays
• need a "set and forget" solution that runs silently in the background

🚀 Core Features

Smart Content Discovery

The bot monitors a configurable list of RSS feeds. For every new entry found, it triggers your GoToSocial instance to fetch and federate the post. This makes the content available for your local users and populates your instance's database with new remote profiles and statuses.

Efficient Resource Management

Unlike many other fetchers, GTS-Federator is designed with a "Single User" philosophy. It uses a persistent HTTP session and a local JSON-based memory to ensure that your instance isn't hammered with redundant requests.

Real-Time Analytics

After every run, the bot provides a clean summary of its activity:

• Runtime: How long the discovery took.
• New Posts: Number of successfully federated statuses.
• Instance Growth: Tracking how many new Fediverse domains your instance has discovered through the process.

Adaptive Pausing & Timezone Support

The bot calculates its next run based on your local time. With built-in timezone support, the logs will always show you exactly when the next discovery cycle starts, matching your local wall clock.

Production-Ready Dockerization

The entire application is container-native. It runs as a non-root user for enhanced security and can be deployed in seconds using Docker Compose.

🧠 Design Philosophy

GTS-Federator follows a few key principles:

• Keep it lightweight – Written in clean Python, utilizing minimal RAM and CPU.
• Zero-Maintenance – Once configured, it handles rate limits, connection timeouts, and state persistence automatically.
• Privacy First – No external tracking. The bot only communicates with your instance and the RSS sources you define.
• Transparency – Clear, human-readable logs that tell you exactly what is happening.

⚙️ Configuration (Environment Variables)

The bot is configured via environment variables. Create a .env file in your project directory using the following parameters:

Variable	Description	Default / Example
Basics
GTS_SERVER_URL	The full URL of your GoToSocial instance.	https://social.domain.tld
GTS_ACCESS_TOKEN	Your application's Access Token (needs read/search scopes).	YOUR_SECRET_TOKEN
Performance
FETCH_INTERVAL	Time the bot sleeps between discovery runs (e.g., 30m, 1h).	30m
MAX_POSTS_PER_RUN	Maximum number of new posts to process per RSS feed per run.	25
DELAY_BETWEEN_REQUESTS	Delay in seconds between API calls to prevent rate limiting.	1
REQUEST_TIMEOUT	Seconds to wait for responses from external servers.	30
Identity & Logs
LOG_LEVEL	Level of logging detail (DEBUG, INFO, WARNING, ERROR).	INFO
USER_AGENT	Custom User-Agent to identify your bot to remote instances.	GTS-Federator/1.0...
Paths
RSS_URLS_FILE	Internal path to the feed list (change only if necessary).	/app/rss_feeds.txt
DATABASE_PATH	Internal path to the JSON state file (change only if necessary).	/app/data/processed_urls.json

📦 Installation

Preparation

Before deploying, you need to set up the directory structure. This ensures the bot can save its "memory" and find your configuration.

1. Create the Project Folder: Create a main directory (e.g., gts-federation).
2. Create the Data Subfolder: Inside that folder, create a subfolder named data. This is where the bot stores its database (processed_urls.json).
3. Place your Files: Put your compose.yaml, .env, and rss_feeds.txt into the main directory.

Folder Structure:

Your final structure should look like this:

gts-federation/
├── data/               <-- Subfolder for the database (Required)
├── .env                <-- Your credentials & settings
├── compose.yaml        <-- Docker configuration
└── rss_feeds.txt       <-- Your list of RSS feeds

Note on Permissions:

Ensure the data folder is writable. If you are using a specific UID (e.g., on a Synology NAS), assign ownership to that user: chown -R 1026:100 ./data

Compose.yaml

version: "3"

services:
  gts-federation:
    image: domoel/gts-federator:latest
    container_name: gts-federator
    #user: 1026:100 # If you run into permission issues with the 'data' folder, make sure to set the correct UID/GID for your system.
    volumes:
      - ./data:/app/data
      - ./rss_feeds.txt:/app/rss_feeds.txt:ro
    environment:
      - TZ=Europe/Berlin # Change to your local timezone.
    env_file:
      - .env
    restart: always

You can download the docker image on Docker Hub