LycheeMem
★ 236
vs
semble
★ 4.6k
LycheeMem vs semble
LycheeMem: LycheeMem is a compact memory framework for LLM agents that organizes memory into working, semantic, and procedural stores. It features a four-stage pipeline (WMManager, SearchCoordinator, SynthesizerAgent, ReasoningAgent) with a background ConsolidatorAgent, and supports multi-channel retrieval (FTS, vector, tag, temporal). It integrates via API, OpenClaw plugin, and MCP protocol.; semble: Semble is a high-performance code search library designed for AI agents, providing instant access to precise code snippets. It offers significantly faster indexing and querying compared to transformer models, achieving 99% of their retrieval quality while running entirely on CPU without external dependencies.
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TL;DR
Choose LycheeMem if…Persistent long-term memory for LLM-based agents
Choose semble if…Enhancing AI agents (e.g., Claude Code, Cursor, Codex) with fast and accurate code search capabilities
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Side-by-Side Comparison
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Features
LycheeMem01Efficient conversational memory with dual-threshold token budget
02Structured semantic memory with 7 typed MemoryRecords and Record Fusion
03Action-aware search planning and multi-dimensional relevance scoring
04Procedural memory with skill store and HyDE retrieval
05Modular pipeline with synchronous stages and asynchronous background consolidation
semble01Fast performance on CPU (indexes in ~250ms, queries in ~1.5ms)
02High accuracy (NDCG@10 of 0.854), comparable to transformer models
03Supports indexing local paths and remote Git repositories
04Functions as an MCP server for various AI agents
05Zero setup, no API keys, GPU, or external services required
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Use Cases
LycheeMem↳Persistent long-term memory for LLM-based agents
↳Context-aware chatbots with adaptive memory retrieval
↳Automated memory consolidation and skill extraction from conversations
semble↳Enhancing AI agents (e.g., Claude Code, Cursor, Codex) with fast and accurate code search capabilities
↳Searching local or remote codebases for specific code snippets based on natural language or code queries
↳Finding semantically similar code sections related to a given file path and line number
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Best For
LycheeMemTrendingMemory & Context
sembleCode AssistantRAG / Knowledge Base
FAQ
FAQ
What is the difference between LycheeMem and semble?
Both LycheeMem and semble are in the Memory & Context category. LycheeMem has 236 stars, while semble has 4.6k stars.
Which is better, LycheeMem or semble?
The best choice depends on your use case. Choose LycheeMem if Persistent long-term memory for LLM-based agents, and semble if Enhancing AI agents (e.g., Claude Code, Cursor, Codex) with fast and accurate code search capabilities.
Is LycheeMem free or open source?
Yes, LycheeMem is open source on GitHub (Apache-2.0).
Is semble free or open source?
Yes, semble is open source on GitHub (MIT).
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