by EverMind-AI · MCP Server · ★ 3.5k
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![banner-gif][banner-gif] [![][arxiv-badge]][arxiv-link] [![Docker][docker-badge]][docker] [![Ask DeepWiki][deepwiki-badge]][deepwiki] [![License][license-badge]][license] Share EverMemOS Repository [![][share-x-shield]][share-x-link] [![][share-linkedin-shield]][share-linkedin-link] [![][share-reddit-shield]][share-reddit-link] [![][share-telegram-shield]][share-telegram-link] -- [Documentation][documentation] • [API Reference][api-docs] • [Demo][demo-section] [![English][lang-en-badge]][lang-en-readme] [![简体中文][lang-zh-badge]][lang-zh-readme] [!IMPORTANT] ### Memory Sparse Attention Check out our latest papar Memory Sparse Attention - A scalable, end-to-end trainable latent-memory framework for 100M token contexts. - Scalable sparse attention + document-wise RoPE (parallel/global) achieving near-linear complexity in both training and inference. - KV cache compression
| Stars | 3,457 |
| Forks | 361 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 56.356/100 |
| Open Issues | 77 |
| Last Updated | 2026-03-30 |
| Created | 2025-10-28 |
| Platforms | mcp, python |
| Est. Tokens | ~2276k |
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EverMemOS is A memory OS that makes your OpenClaw agents more personal while saving tokens.. It is categorized as a MCP Server with 3.5k GitHub stars.
EverMemOS is primarily written in Python. It covers topics such as agent-memory, agentic-ai, ai.
You can find installation instructions and usage details in the EverMemOS GitHub repository at github.com/EverMind-AI/EverMemOS. The project has 3.5k stars and 361 forks, indicating an active community.
EverMemOS is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to EverMemOS on Agent Skills Hub include MemOS, honcho, m_flow. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.