Fredy
❤️ Fredy - [F]ind [R]eal [E]state [D]amn Eas[y] - Fredy keeps searching for new apartments, houses, and flats in Germany on platforms like ImmoScout24, Immowelt, Immonet, eBay Kleinanzeigen, and WG-Gesucht and instantly delivers the results to you via Slack, Telegram, Email, Discord or ntfy, so you can focus on the more important things in life ;)
Install / Use
/learn @orangecoding/FredyREADME
Fredy 🏡 – Your Self-Hosted Real Estate Finder for Germany
Finding an apartment or house in Germany can be stressful and
time-consuming.
Fredy makes it easier: it automatically scrapes ImmoScout24,
Immowelt, Immonet, eBay Kleinanzeigen, and WG-Gesucht and notifies you
instantly via Slack, Telegram, Email, ntfy, discord and more when new
listings appear.
With a modern architecture, Fredy provides a clean Web UI, removes duplicates across platforms, and stores results so you never see the same listing twice.
✨ Key Features
- 🏠 Scrapes ImmoScout24, Immowelt, Immonet, eBay Kleinanzeigen, WG-Gesucht
- ⚡ Instant notifications: Slack, Telegram, Email (SendGrid, Mailjet), ntfy, discord
- 🔎 Uses the ImmoScout Mobile API (reverse engineered)
- 🌍 Runs anywhere: Docker, Node.js, self-hosted
- 🖥️ Intuitive Web UI to manage searches
- 🎯 Easy to use thanks to a user-friendly Web UI
- 🔄 Deduplication across platforms
- ⏱️ Customizable search intervals
🤝 Sponsorship 
I maintain Fredy and other open-source projects in my free time.
If you find it useful, consider supporting the project 💙
Fredy is proudly backed by the JetBrains Open Source Support Program.
<picture> <source media="(prefers-color-scheme: dark)" srcset="https://www.jetbrains.com/company/brand/img/logo_jb_dos_3.svg"> <source media="(prefers-color-scheme: light)" srcset="https://resources.jetbrains.com/storage/products/company/brand/logos/jetbrains.svg"> <img alt="Jetbrains Open Source" src="https://resources.jetbrains.com/storage/products/company/brand/logos/jetbrains.svg"> </picture>👨🏫 Demo
You can try out Fredy here: Fredy Demo
🚀 Quick Start
With Docker
[!NOTE] In order to start Fredy, you must provide a config.json. As a start, use the one in this repo: https://github.com/orangecoding/fredy/blob/master/conf/config.json
docker run -d --name fredy \
-v fredy_conf:/conf \
-v fredy_db:/db \
-p 9998:9998 \
ghcr.io/orangecoding/fredy:master
Logs:
docker logs fredy -f
Manual (Node.js)
- Requirement: Node.js 22 or higher
- Install dependencies and start:
yarn
yarn run start:backend # in one terminal
yarn run start:frontend # in another terminal
👉 Open http://localhost:9998
With Unraid
Should you use Unraid, you can now install Fredy from the community store :)
Default Login:
- Username:
admin - Password:
admin
📸 Screenshots
| Fredy Maps View | Dashboard | Found Listings |
|--------------------------------------------------|-----------------------------------------------------------------------|-----------------------------------------------------------------------------|
| 
| 
| 
|
🧩 Core Concepts
Fredy is built around three simple concepts:
Provider 🌐
A provider is a real-estate platform (e.g. ImmoScout24, Immowelt,
Immonet, eBay Kleinanzeigen, WG-Gesucht).
When you create a job, you paste the search URL from the platform into
Fredy.
⚠️ Always make sure the search results are sorted by date, so Fredy
picks up the newest listings first.
Adapter 📡
An adapter is the channel through which Fredy notifies you (Slack,
Telegram, Email, ntfy, discord ...).
Each adapter has its own configuration (e.g. API keys, webhook URLs).
You can use multiple adapters at once --- Fredy will send new listings
through all of them.
Job 📅
A job combines providers and adapters.
Example: "Search apartments on ImmoScout24 + Immowelt and send results
to Slack + Telegram."
Jobs run automatically at the interval you configure (see
/conf/config.json).
MCP Server 🤖
Starting with V20, Fredy ships with a built-in **MCP Server **. This allows you to connect Fredy to LLMs (like Claude, ChatGPT, or local models via LM Studio) and query your real estate data using natural language. The local LLM can even enrich existing listings by checking the listing online.
For more information on how to set it up and use it, please refer to the MCP Readme.
Immoscout
Immoscout has implemented advanced bot detection. In order to work around this, we are using a reversed engineered version of their mobile api. See Immoscout Reverse Engineering Documentation
Analytics
Fredy is completely free (and will always remain free). However, it would be a huge help if you’d allow me to collect some analytical data.
Before you freak out, let me explain...
If you agree, Fredy will send a ping once every 6 hours to my internal tracking project (Will be open sourced soon).
The data includes: names of active adapters/providers, OS, architecture, Node version, and language. The information is entirely anonymous and helps me understand which adapters/providers are most frequently used.</p>
Thanks🤘
🛠️ Development
Development Mode
yarn run start:backend:dev
yarn run start:frontend:dev
You should now be able to access Fredy from your browser. Check your Terminal to see what port the frontend is running on.
Run Tests
yarn run test
📐 Architecture
flowchart TD
subgraph Jobs["Jobs"]
A1["Job 1"]
A2["Job 2"]
A3["Job 3"]
end
subgraph Providers["Providers"]
C1["Provider 1"]
C2["Provider 2"]
C3["Provider 3"]
end
subgraph NotificationAdapters["Notification Adapters"]
F1["Adapter 1"]
F2["Adapter 2"]
end
A1 --> B["FredyPipelineExecutioner"]
A2 --> B
A3 --> B
B --> C1 & C2 & C3
C1 --> D["Similarity Check"]
C2 --> D
C3 --> D
D --> E{"Duplicate?"}
E -- No --> F1
F1 --> F2
👐 Contributing
Thanks to everyone who has contributed!
<a href="https://github.com/orangecoding/fredy/graphs/contributors"><img src="https://contrib.rocks/image?repo=orangecoding/fredy" /></a>
See the Contributing Guide.
