by LycheeMem · MCP Server · ★ 1.1k
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LycheeMem 中文 | English LycheeMem is a compact memory framework for LLM agents. It starts from efficient conversational memory—through structured organization, lightweight consolidation, and adaptive retrieval—and gradually extends toward action-aware, usage-aware memory for more capable agentic systems. News • Memory Architecture • Pipeline • Quick Start • Web Demo • OpenClaw Plugin • MCP • API Reference 🔥 News [04/03/2026] The project now supports installation via . You can easily start the service from anywhere using ! [03/30/2026] We evaluated LycheeMem on PinchBench with the OpenClaw plugin: compared to OpenClaw's
| Stars | 1,114 |
| Forks | 15 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 59.437522345646/100 |
| Open Issues | 2 |
| Last Updated | 2026-07-07 |
| Created | 2026-03-23 |
| Platforms | mcp, python |
| Est. Tokens | ~20k |
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LycheeMem is Lightweight Long-Term Memory for LLM Agents.. It is categorized as a MCP Server with 1.1k GitHub stars.
LycheeMem is primarily written in Python. It covers topics such as agent-memory, ai, ai-memory.
You can find installation instructions and usage details in the LycheeMem GitHub repository at github.com/LycheeMem/LycheeMem. The project has 1.1k stars and 15 forks, indicating an active community.
LycheeMem is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to LycheeMem on Agent Skills Hub include swarmclaw, Ori-Mnemos, YourMemory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.