Project-MONAI/MONAI
AI Toolkit for Healthcare Imaging
Star History
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+219
STARS · LAST 30 DAYS
7
PER DAY
#200
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +49 | +219 | +630 |
| Per day | 7 | 7 | 7 |
| Forks gained | +8 | +33 | +82 |
MONAI gained 219 stars in the last 30 days, about 7 a day, and now has 8.8K. It is about 7 years old and has averaged roughly 1.3K stars a year. It ranks #200 among Python repositories and #1,237 across all languages on GitHubRepo.
Trending Record
1
DAYS ON TRENDING
#3518
BEST RANK
Oct 6, 2026
FIRST APPEARANCE
Active
STATUS TODAY
MONAI has maintained a continuous presence across global trending indexes, peaking at #3518. Below is the 30-day activity profile:
💡 Overview
MONAI is an open-source project written in Python: AI Toolkit for Healthcare Imaging.
Engineered for speed, consistency, and developer ease, it solves common hurdles in deep-learning, healthcare-imaging, medical-image-computing. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install MONAI⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
MONAI coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with MONAI.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install MONAI using your package manager: `pip install MONAI`
Initialize your project workspace or configuration file for MONAI.
Import MONAI into your codebase or invoke it directly from your terminal.
Execute your test suite or run `MONAI --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
Project-MONAI/MONAI is currently ranked #1,237 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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|---|---|---|---|---|
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| #1,236 | ariga/atlas | Go | ★ 8.8K | Compare ↗ |
| #1,237 | Project-MONAI/MONAI This Project | Python | ★ 8.8K | |
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Frequently Asked Questions
What does MONAI do? +
AI Toolkit for Healthcare Imaging
What language is MONAI written in? +
The primary language is Python. Topics include: deep-learning, healthcare-imaging, medical-image-computing, medical-image-processing, monai.
Is MONAI actively maintained? +
Yes, the last recorded push was on Oct 6, 2026 with 508 open issues being tracked.
How many stars does MONAI have? +
MONAI has 8,755 stars and 1,644 forks on GitHub.
How does MONAI rank among GitHub repositories? +
With 8,755 stars, Project-MONAI/MONAI is ranked #1,237 globally across all repositories tracked on GitHubRepo and #200 among Python projects.
What license is MONAI distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
