dense-mem
★ 39
vs
mnemo
★ 12
dense-mem vs mnemo
dense-mem: Dense-Mem is a self-hosted, durable memory layer for AI agents designed to preserve evidence, detect conflicts, and prevent silent rewriting of facts. It provides typed claims, verification gates, server-side embeddings, and structured recall, enabling host LLMs to focus on conversation and judgment while Dense-Mem manages memory state.; mnemo: Mnemo is an open, free, and unlimited persistent AI memory system featuring hybrid search and embedded synchronization. It integrates full-text search with vector search, temporal decay, and importance boosting for advanced retrieval.
01
TL;DR
dense-memMemory & Context · ★ 39
Providing durable and verifiable memory for AI agents in complex tasks.
mnemoMemory & Context · ★ 12
Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making.
02
Side-by-Side Comparison
Field
dense-memmnemoCategory
Memory & Context
Memory & Context
Stars
★ 39
★ 12
License
Apache-2.0
Apache-2.0
Install Command
mkdir dense-mem-local && cd dense-mem-local && curl -fsSLo docker-compose.yml https://raw.githubusercontent.com/markhuangai/dense-mem/main/examples/docker-compose.base.yml && curl -fsSLo .env.example https://raw.githubusercontent.com/markhuangai/dense-mem/main/examples/.env.example && cp .env.example .env && docker compose up -d
/plugin marketplace add n24q02m/claude-plugins && /plugin install mnemo-mcp@n24q02m-plugins
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
AI Memory, Knowledge Graph, Conflict Detection
AI Memory, Hybrid Search, Vector Database
03
Features
dense-mem01First-class evidence provenance, tracing memories from source fragments to facts.
02Facts pass through typed claims, verification, and promotion gates.
03Explicit conflict detection where comparable conflicts return clarification tasks, preventing silent overwrites.
04Clear responsibility boundary: host LLM judges, Dense-Mem manages durable state, gates, and audit metadata.
05Self-hosted with operator control over storage, team isolation, API keys, and data egress boundaries.
mnemo01Hybrid retrieval combining full-text search (FTS5) and vector search, fused via Reciprocal Rank Fusion, then re-ranked with temporal decay and importance boost.
02Automatic entity extraction and relation tracking to build a temporal knowledge graph, boosting top search results by graph proximity.
03Multi-machine sync via Google Drive with JSONL-based merge sync, and end-to-end encrypted passport sync using AES-256-GCM and Argon2id for secure cross-device bootstrap.
04LLM-driven compression of older memories and LLM summarization of related memories for STM-to-LTM consolidation, achieving significant token reduction.
05Zero-config local setup using Fastretrieval's built-in Qwen3 ONNX embedding and reranking models, requiring no external API keys for basic operation.
04
Use Cases
dense-mem↳Providing durable and verifiable memory for AI agents in complex tasks.
↳Building enterprise AI systems that require strong data governance, auditability, and trusted knowledge.
↳Resolving conflicting information in AI knowledge bases through user clarification and structured processes.
↳Enhancing AI agent reliability and explainability by preserving evidence and preventing silent fact rewriting.
mnemo↳Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making.
↳Building and querying a temporal knowledge graph to understand historical states and relationships of entities within an AI system's memory.
↳Synchronizing AI memory across multiple machines or devices securely, enabling a consistent knowledge base for agents.
↳Improving the efficiency of LLM interactions by compressing older memories and consolidating related information.
↳Integrating with various AI clients (e.g., Claude Code, Gemini CLI, Cursor) as an MCP server for advanced memory management.
FAQ
FAQ
What is the difference between dense-mem and mnemo?
Both dense-mem and mnemo are in the Memory & Context category. dense-mem has 39 stars, while mnemo has 12 stars.
Which is better, dense-mem or mnemo?
The best choice depends on your use case. Choose dense-mem if Providing durable and verifiable memory for AI agents in complex tasks., and mnemo if Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making..
Is dense-mem free or open source?
Yes, dense-mem is open source on GitHub (Apache-2.0).
Is mnemo free or open source?
Yes, mnemo is open source on GitHub (Apache-2.0).
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