Memmy

What is Memmy?

Memmy is a local-first AI memory platform that acts as a shared “brain” for all your AI tools. Instead of starting from scratch every time you switch between tools like Cursor, Claude, or Codex, Memmy stores your past conversations, preferences, and project context in one place—and lets every AI access it when needed. It works by scanning your authorized AI history, organizing it into structured, searchable memory, and then injecting the most relevant context into future tasks. Beyond memory, it also acts as its own AI agent—able to continue tasks, merge ideas, and manage workflows across tools. With a desktop app, CLI, and API, Memmy is designed for developers and heavy AI users who want consistent context, faster workflows, and a more personalized AI experience across every tool they use.

Launched in 2026 by Zhiqi Xu and the MemTensor team, Memmy solves the fragmented context problem in multi-agent workflows. Operating with a 100% on-device, local-first architecture where conversational data is never uploaded to remote servers without explicit consent, Memmy functions both as a shared memory layer and as an autonomous agent runtime. It is free and open-source (FOSS) with free starter trial tokens and Bring-Your-Own-Key (BYOK) API support.

• Founder / Creator: Zhiqi Xu (MemTensor)
• Launch Year: 2026

Use Cases:

• Relaying active project context, design constraints, and decisions when switching from Cursor to Claude Code or Codex
• Remembering coding preferences, stylistic rules (e.g., “use Tauri instead of Electron”), and repository conventions permanently
• Capturing “failure memory” when an approach dead-ends, preventing other AI agents from repeating the same debugging rabbit holes
• Executing direct background tasks via the Memmy agent runtime (synthesizing weekly technical decisions, merging plans, drafting docs)
• Searching, managing, and curating your personal on-device knowledge vault across CLI, TUI, and desktop interfaces

Technology:

• Four-layer cognitive memory architecture: L1 Trace (raw turns), L2 Policy (distilled preferences/avoidance), L3 World Model (project state), and Crystallized Skills (reusable SOPs)
• Local-first background system services (memmy-memory and memmy-gateway) running over local RPC and OpenAI-compatible API endpoints (:18990)
• Cross-agent skill integration hooks supporting Claude Code, Cursor, Codex, OpenClaw, and Hermes Agent

Target Users:

• Software engineers and full-stack developers switching between multiple AI coding assistants and CLI agents
• AI power users and prompt engineers seeking cross-platform memory continuity without manual copy-pasting
• Privacy-conscious developers who require 100% on-device data sovereignty and local encrypted storage
• Open-source contributors and agentic workflow builders experimenting with multi-agent orchestration

Acquisition: Operates as an open-source project and independent developer platform (MemTensor)

Key features of Memmy

Memmy's key features are

• Four-Layer Cognitive Memory Hierarchy: Automatically structures raw conversations into L1 Traces, distills experiences into L2 Policies, abstracts project constraints into L3 World Models, and crystallizes proven workflows into reusable Skills.
• Cross-Agent Context Relay: Seamlessly injects relevant preferences, architectural rules, and project milestones into whichever agent you are actively using (Cursor, Claude Code, Codex, OpenClaw).
• Failure Memory & Avoidance Guidance: Logs dead-end debugging approaches and technical failures so future agents avoid repeating the same mistaken pathways.
• 100% Local-First Storage & Privacy: All memory graphs and vector indices reside strictly on your local machine, ensuring private API keys and confidential proprietary code never leave your device.
• Dual Role (Memory Hub + Autonomous Agent): Beyond passive memory indexing, Memmy acts as a capable agent that can execute multi-turn terminal commands, summarize meeting notes, and merge project plans.
• CLI, TUI, and Desktop App Workspaces: Interact via an intuitive desktop GUI, an interactive terminal user interface (TUI), or headless scriptable CLI commands (memmy-memory).
• OpenAI-Compatible Local Gateway: Exposes a standardized local API server (:18990) enabling any custom tool, plugin, or script to query and append to your memory graph.
• Granular Granular Access Controls: View, search, edit, or delete specific memories at any time, and configure exact permission boundaries per agent.

Memmy Pricing

Memmy is free and open source, offering trial tokens for new users alongside a flexible Bring-Your-Own-Key (BYOK) model.

Open Source / BYOK (100% Free Core):

• $0 / Free Forever: Full access to desktop app (macOS, Windows, Linux), CLI, TUI, local memory daemon, and multi-agent plugins
• Free trial tokens included upon signup to test cloud agent runtime tasks
• Unlimited local memory indexing and retrieval using your own provider API keys (OpenAI, Anthropic, DeepSeek, Ollama)

Disclaimer: For the latest desktop builds, community roadmap milestones, and GitHub repository updates, please visit the official Memmy portal at memmy.bot or github.com/MemTensor/memmy-agent.

Who is using Memmy?

Memmy is used by developers and AI power users globally, including

• Multi-Tool Software Engineers: Eliminating repetitive onboarding when moving code tasks between Cursor and Claude Code
• Autonomous Agent Builders: Equipping terminal agents (Codex, OpenClaw, Hermes) with persistent, self-evolving memory
• Technical Leads & Architects: Preserving persistent project constraints, tech-stack decisions, and coding standards
• Privacy-Conscious Programmers: Maintaining a completely on-device personal knowledge base without third-party data tracking

Best Memmy Alternatives

Some of the strongest Memmy alternatives include

• Mem0 (formerly Embedchain)
• Pieces for Developers
• Zep (Memory for AI Assistants)
• Letta (MemGPT)
• TypingMind (Memory Plugins)
• Rewind AI / Limitless

Pros and Cons of Memmy

Pros

• Solves context loss across multiple AI tools by serving as a unified, shared memory hub
• Local-first architecture guarantees your proprietary codebase and prompts never leak to remote memory servers
• Four-layer cognitive structure (Trace → Policy → World Model → Skill) organizes knowledge intelligently rather than dumping raw chats
• Shared failure memory prevents AI agents from getting trapped in identical debugging loops
• Completely open-source with desktop, TUI, and scriptable CLI options

Cons

• Requires connecting personal LLM API keys (BYOK) once initial trial tokens are consumed
• Initial setup of CLI hooks and systemd services requires comfort with developer terminal commands
• Ecosystem integrations are actively expanding; non-coding apps (e.g., Notion, Obsidian) are still in development

Why Choose Memmy?

Every AI coding assistant today operates in a total vacuum—forgetting what you discussed the moment a chat window closes. Memmy gives you a permanent, sovereign memory layer that unites all your AI tools.

• Stops you from typing the same background explanations, preferences, and tech rules over and over
• Ensures your context moves with you whether you code in Cursor, Claude Code, or terminal CLIs
• Keeps all your personal intelligence safely on your own computer under your direct control
• Acts as an active agent coworker that turns past discussions into structured project documentation

Memmy vs. Competitors

The main difference between Memmy, Mem0, Pieces for Developers, and Letta (MemGPT) lies in its developer-first multi-agent focus and local-first execution. While Mem0 is primarily a cloud API for developer apps, and Pieces is an on-device snippet manager, Memmy focuses specifically on bridging coding assistants (Cursor, Claude Code, Codex) via a 4-layer cognitive memory pipeline and local daemon services.

How do we rate Memmy?

Memmy Review

Memmy delivers an elegant and long-overdue solution to one of the biggest headaches in modern AI development: context fragmentation across tools. By creating an intelligent, local-first memory layer that abstracts past conversations into structured preferences, world models, and failure avoidance policies, Memmy ensures that switching between Cursor, Claude Code, and terminal agents feels continuous and cohesive. For developers and AI practitioners tired of starting from scratch with every new prompt, Memmy is an essential productivity upgrade.

Conclusion

Memmy is a powerful and forward-thinking platform that solves one of the biggest problems in modern AI workflows—context loss across tools. Instead of treating each AI interaction as a fresh start, it creates a shared memory layer that allows multiple AI agents (like Claude, Codex, and Cursor) to remember your preferences, decisions, and ongoing projects. Its biggest strength lies in its local-first memory system. All data is stored on your device, giving you full control while still enabling advanced features like memory retrieval, cross-agent context sharing, and task continuation. This makes it especially valuable for developers and power users who rely on multiple AI tools daily. While it requires setup and is still evolving, the concept is highly impactful. Memmy represents the future of AI workflows—where tools don’t just respond, but remember, adapt, and collaborate over time.