Memmy.bot NEW

Memmy organizes AI conversation history into structured, searchable local memory for developers, data scientists, product teams, and frequent AI users.It scans authorized local AI tool histories (examples.

Cursor, Claude, Codex), deduplicates entries, and extracts preferences, technical decisions, and project context.Memmy preserves context across tools so users can switch models or agents without losing project state, progress, or personalized settings.

The agent memory manager merges plans, resumes unfinished tasks, and injects relevant memory into a selected AI tool on demand to streamline workflows.All memory is stored on-device by default, with explicit authorization required for scans and user controls to view, export, or delete stored items.

Desktop apps are available for macOS (including ARM64) and Windows x64; the project is open-source with source code on GitHub and active community channels for issues and contributions.

Key Features

• Structured, searchable local memory for AI conversation history
• Scans authorized local AI tool histories, deduplicates entries, and extracts preferences, technical decisions, and project context
• Preserves context across tools to allow model/agent switching without losing project state, progress, or personalized settings
• Agent memory manager merges plans, resumes unfinished tasks, and injects relevant memory into a selected AI tool on demand
• On-device storage by default with explicit authorization for scans and user controls to view, export, or delete stored items

Use Cases

• Maintain continuous cross-model development context with Memmy by storing authorized AI conversations on-device (macOS/Windows), deduplicating entries, extracting decisions, preferences and action items, and injecting relevant memory so engineers can seamlessly resume unfinished tasks across models
• Build a private personal AI assistant using Memmy's open-source on-device memory manager—keep conversation history local, capture user preferences and routines, deduplicate and surface relevant context to any model without cloud exposure to power personalized automations
• Streamline product management and research workflows by using Memmy to extract project context and distilled decisions from AI chats, create searchable local memory for stakeholders, resume stalled tasks, and auto-inject concise briefings into different models for faster handoffs

Who is it for?

• Developers
• Product designers
• Product managers
• Data science students
• Tech hobbyists