Ross ROSS = Recommend OSS · open-source software intelligence for agents

MemTensor/memmy-agent

🍙 A personal AI agent & local memory hub for all AI agents, gives every AI one shared, fully controlled memory and persistent context — all AI remember the same you. Now supports Claude Code, Codex, OpenClaw and Hermes Agent etc. observed · 2026-09-03

github.com/MemTensor/memmy-agent · homepage · TypeScript · MIT (permissive) observed · 2026-09-03

Health v2 · maintenance only

80/100

  • Activity 100
  • Release rhythm 99
  • Longevity 3

Flags: young

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 4.0
  • age_days: 48
  • days_rel: 7
  • days_push: 0
  • n_releases_24m: 11

Full methodology

Adoption not part of the score

1232 stars · 109 forks observed · 2026-09-03

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Memmy is a personal AI agent and local memory hub that gives every AI agent (Claude Code, Codex, Cursor, OpenClaw, etc.) a shared, locally controlled long-term memory and persistent context. It ships as a desktop app, CLI, and HTTP/OpenAI-compatible API, powered by a MemOS-based memory engine with local SQLite storage.

Use cases

  • share one memory across Claude Code, Codex, and Cursor
  • continue unfinished tasks when switching between AI coding agents
  • turn scattered AI chat history into structured personal memory
  • remember my coding preferences so I never repeat them to new agents
  • hand tasks directly to a personal AI agent that knows my context
  • inject relevant project context into whichever agent I'm using
  • run a local memory service for external agents via CLI or API
  • consolidate weekly technical decisions into a document automatically

When to choose

  • you work with multiple AI agents daily and want shared, persistent context
  • you want local-first memory storage with BYOK model support
  • you need cross-agent task continuity without re-explaining your project
  • you want an agent runtime with MCP, scheduled tasks, and skills built in

When to avoid

  • you need a purely cloud-hosted memory service with team collaboration
  • you only use a single AI tool and don't need cross-agent memory
  • you require fully offline operation without any account or trial tokens
  • you need a lightweight library to embed memory in your own app rather than a standalone app

Facets

application · maturity active

agent-framework mcp rag chatbot cli search-engine sdk large-language-models developer-tools windows cli cross-platform long-term-memory memory-hub cross-agent-context desktop-pet local-first byok claude-code codex cursor openclaw memos sqlite tui task-continuity ai-agents automation macos desktop typescript

3 sources

Member repositories

RepositoryRoleHealth v2
MemTensor/memmy-agentmain80

For agents

markdown · JSON · MCP: product_card(name="MemTensor/memmy-agent")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem