memory-system-v2-1-0-0Fast semantic memory system with JSON indexing, auto-consolidation, and <20ms search. Capture learnings, decisions, insights, events. Use when you need persi...
Install via ClawdBot CLI:
clawdbot install Sieyer/memory-system-v2-1-0-0Install jq via Homebrew:
brew install jqRequires:
Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://github.com/austenallred/memory-system-v2Audited Apr 17, 2026 · audit v1.0
Generated Mar 21, 2026
A development team uses the memory system to capture technical learnings, architectural decisions, and bug insights across projects. It enables quick recall of past solutions and patterns during code reviews or new feature planning, reducing redundant research and ensuring consistency in decision-making.
A creative agency employs the memory system to log client interactions, design insights, and project milestones. This helps teams recall client preferences and past feedback efficiently, improving communication and delivering more personalized creative outputs over time.
An individual uses the memory system to track personal insights, daily decisions, and learning milestones related to skill development or habit formation. It supports self-reflection and goal tracking by providing a searchable history of progress and key realizations.
A customer support team integrates the memory system to capture common issues, resolution insights, and interaction patterns with users. This allows agents to quickly search past cases for similar problems, speeding up response times and improving service quality.
Researchers or students use the memory system to document experimental insights, literature review decisions, and event-based milestones in their work. It facilitates easy retrieval of key findings and methodologies, enhancing collaboration and reducing information loss across long-term projects.
Offer a basic version of the memory system as a free tool for individual users, with premium features like advanced analytics, team collaboration, and cloud sync available through subscription plans. Revenue is generated from monthly or annual subscriptions, targeting small to medium-sized businesses.
License the memory system to large organizations with needs for on-premise deployment, custom integrations, and enhanced security. Revenue comes from one-time licensing fees, annual maintenance contracts, and custom development services tailored to specific enterprise workflows.
Provide consulting services to help businesses integrate the memory system into their existing tools and processes, such as CRM or project management software. Revenue is generated from hourly or project-based consulting fees, along with training workshops and support packages.
💬 Integration Tip
Integrate the memory system by setting up automated capture scripts in your workflow tools, such as linking it to code commits or meeting notes, and ensure regular consolidation to maintain search efficiency.
Scored Apr 19, 2026
Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready.
Search and analyze your own session logs (older/parent conversations) using jq.
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linkin...
Audit, clean, and optimize Clawdbot's vector memory (LanceDB). Use when memory is bloated with junk, token usage is high from irrelevant auto-recalls, or setting up memory maintenance automation.
Infinite organized memory that complements your agent's built-in memory with unlimited categorized storage.
You MUST use this for gathering contexts before any work. This is a Knowledge management for AI agents. Use `brv` to store and retrieve project patterns, dec...