squish-memory logo
squish-memory
★ 12
vs
mnemo logo
mnemo
★ 12

squish-memory vs mnemo

squish-memory: Squish is a local-first, open-source memory system designed for AI agents, preventing them from forgetting past decisions, constraints, and preferences. It integrates with various coding agents and offers CLI, an MCP server, and a desktop app for managing and recalling relevant context.; 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

squish-memory logo
squish-memoryMemory & Context · ★ 12

Enhancing AI Agent Performance by Providing Persistent Memory

mnemo logo
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
squish-memory logosquish-memory
mnemo logomnemo
Category
Memory & Context
Memory & Context
Stars
★ 12
★ 12
License
NOASSERTION
Apache-2.0
Install Command
npm install -g squish-memory && squish install --all
/plugin marketplace add n24q02m/claude-plugins && /plugin install mnemo-mcp@n24q02m-plugins
Updated
3w ago
2d ago
Open Source
Yes
Yes
Tags
AI Agent Memory, Context Management, Local-first
AI Memory, Hybrid Search, Vector Database
03

Features

squish-memory logosquish-memory
01Unified Memory System for AI Agents
02Local-first Storage with SQLite and Cloud Sync Option
03Automatic Context Injection for Agents (50-200 tokens)
04Multiple Interfaces: CLI, MCP Server, and Desktop App
05Compatibility with Various Coding Agents via MCP Standard
mnemo logomnemo
01Hybrid 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

squish-memory logosquish-memory
↳Enhancing AI Agent Performance by Providing Persistent Memory
↳Managing and Recalling Development-Specific Knowledge and Preferences
↳Injecting Relevant Context into Coding Assistants like Claude Code or Codex
mnemo logomnemo
↳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 squish-memory and mnemo?
Both squish-memory and mnemo are in the Memory & Context category. squish-memory has 12 stars, while mnemo has 12 stars.
Which is better, squish-memory or mnemo?
The best choice depends on your use case. Choose squish-memory if Enhancing AI Agent Performance by Providing Persistent Memory, and mnemo if Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making..
Is squish-memory free or open source?
Yes, squish-memory is open source on GitHub (NOASSERTION).
Is mnemo free or open source?
Yes, mnemo is open source on GitHub (Apache-2.0).
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