squish-memory

★ 12

state-memory-mcp

★ 48

squish-memory vs state-memory-mcp

Q: Which is better, squish-memory or state-memory-mcp?

By GitHub stars, state-memory-mcp has more community adoption, but the best choice depends on your specific use case.

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.; state-memory-mcp: @putervision/state-memory-mcp is a zero-infrastructure, deterministic Model Context Protocol (MCP) server designed to provide AI coding assistants with a structured, persistent SQLite graph for tracking workflow state. It offers efficient context management, reduces latency by offloading to a local database, and supports multi-agent collaboration with a shared blackboard.

TL;DR

squish-memoryMemory & Context · ★ 12

Enhancing AI Agent Performance by Providing Persistent Memory

Read squish-memory full review →

state-memory-mcpMemory & Context · ★ 48

Providing persistent workflow state to AI coding assistants like Cursor and Copilot

Read state-memory-mcp full review →

Side-by-Side Comparison

Field

squish-memory

state-memory-mcp

Features

squish-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

state-memory-mcp

01Deterministic State Memory & Compact TaskSlices for fast evaluation

02Efficient Context Management & Decision Thresholding to prevent graph bloat

03Multi-Agent Blackboard for shared context and parallel subagent updates

04100% Local & Private architecture, ensuring all state stays within your workspace

05Interactive 3D Visualizer for graph exploration

Use Cases

squish-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

state-memory-mcp

↳Providing persistent workflow state to AI coding assistants like Cursor and Copilot

↳Managing context and decision-making for autonomous agents

↳Facilitating multi-agent collaboration on complex tasks with a shared context store

↳Auditing and tracing agent activities with a tamper-evident event ledger

↳Improving agent efficiency and reducing latency in task retrieval and context processing

FAQ

What is the difference between squish-memory and state-memory-mcp?

Both squish-memory and state-memory-mcp are in the Memory & Context category. squish-memory has 12 stars, while state-memory-mcp has 48 stars.

Which is better, squish-memory or state-memory-mcp?

The best choice depends on your use case. Choose squish-memory if Enhancing AI Agent Performance by Providing Persistent Memory, and state-memory-mcp if Providing persistent workflow state to AI coding assistants like Cursor and Copilot.

Is squish-memory free or open source?

Yes, squish-memory is open source on GitHub (NOASSERTION).

Is state-memory-mcp free or open source?

Yes, state-memory-mcp is open source on GitHub (MIT).

Cloud Infrastructure

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Alternatives to squish-memory →Alternatives to state-memory-mcp →squish-memory details →state-memory-mcp details →

TL;DR

Side-by-Side Comparison

Features

Use Cases

FAQ

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