by joshuaswarren · Agent Tool · ★ 52
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Local-first memory plugin for OpenClaw AI agents. LLM-powered extraction, plain markdown storage, hybrid search via QMD. Gives agents persistent long-term memory across conversations.
| Stars | 52 |
| Forks | 11 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 35.25/100 |
| Open Issues | 1 |
| Last Updated | 2026-04-08 |
| Created | 2026-02-05 |
| Platforms | node |
| Est. Tokens | ~724k |
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openclaw-engram is Local-first memory plugin for OpenClaw AI agents. LLM-powered extraction, plain markdown storage, hybrid search via QMD. Gives agents persistent long-term memory across conversations.. It is categorized as a Agent Tool with 52 GitHub stars.
openclaw-engram is primarily written in TypeScript. It covers topics such as ai-agent, ai-memory, conversational-ai.
You can find installation instructions and usage details in the openclaw-engram GitHub repository at github.com/joshuaswarren/openclaw-engram. The project has 52 stars and 11 forks, indicating an active community.
openclaw-engram is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openclaw-engram on Agent Skills Hub include omega-memory, hipocampus, cognithor. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.