⚡ Executive Summary & Quick Facts
Authoritative Sourcememanto is memanto is an open-source project written in Python: Memory that AI Agents Love!..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), moorcheh-ai/memanto has accumulated 2,366 GitHub stars and 743 forks. It is written in Python, licensed under MIT, and ranks #5,038 globally. It is actively maintained with the latest commit recorded on Nov 11, 2026.”
| Repository | moorcheh-ai/memanto ↗ |
|---|---|
| Primary Category | agent memory |
| Language & Stack | Python |
| Software License | MIT |
| Community Traction | ★ 2.4K stars · ⑂ 743 forks · #5,038 globally |
| Maintenance | ● Active (Last commit: Nov 11, 2026) · 5 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 97/100 · Grade A+Yes, memanto is actively maintained. Continuous telemetry recorded the last code commit on Nov 11, 2026 (1 days ago). Supported by 2,366 stars and 743 community forks, this repository holds a calculated health index of 97/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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+50
STARS · LAST 30 DAYS
2
PER DAY
#738
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +50 | +50 | +180 |
| Per day | 7 | 2 | 2 |
| Forks gained | +5 | +5 | +37 |
memanto gained 50 stars in the last 30 days, about 2 a day, and now has 2.4K. It is about 1 year old and has averaged roughly 2.4K stars a year. It ranks #738 among Python repositories and #5,038 across all languages on GitHubRepo.
Trending Record
42
DAYS ON TRENDING
#597
BEST RANK
Sep 26, 2026
FIRST APPEARANCE
Active
STATUS TODAY
memanto has maintained a continuous presence across global trending indexes, peaking at #597. Below is the 30-day activity profile:
💡 Overview
memanto is an open-source project written in Python: Memory that AI Agents Love!.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-memory, ai-agents, crewai. 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 memanto⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
memanto 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 memanto.
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 memanto using your package manager: `pip install memanto`
Initialize your project workspace or configuration file for memanto.
Import memanto into your codebase or invoke it directly from your terminal.
Execute your test suite or run `memanto --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
moorcheh-ai/memanto is currently ranked #5,038 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #5,033 | MobileFirstLLC/social-media-hacker-list | Rust | ★ 2.4K | Compare ↗ |
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| #5,038 | moorcheh-ai/memanto This Project | Python | ★ 2.4K | |
| #5,038 | countries/countries | Ruby | ★ 2.4K | Compare ↗ |
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Frequently Asked Questions
What does memanto do? +
Memory that AI Agents Love!
Is memanto actively maintained in 2026? +
Yes, memanto is actively maintained. The latest code push was recorded on Nov 11, 2026 (1 days ago). It holds a calculated Maintenance Health Score of 97/100 (A+ rating) with 2,366 stars and 5 open issues.
What language is memanto written in? +
The primary language is Python. Topics include: agent-memory, ai-agents, ai-memory, ai-memory-system, hermes-agent.
How many stars does memanto have? +
memanto has 2,366 stars and 743 forks on GitHub.
How does memanto rank among GitHub repositories? +
With 2,366 stars, moorcheh-ai/memanto is ranked #5,038 globally across all repositories tracked on GitHubRepo and #738 among Python projects.
What license is memanto distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
