vector-memorySmart memory search with automatic vector fallback. Uses semantic embeddings when available, falls back to built-in search otherwise. Zero configuration - works immediately after ClawHub install. No setup required - just install and memory_search works immediately, gets better after optional sync.
Install via ClawdBot CLI:
clawdbot install bluepointdigital/vector-memoryGrade Excellent — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
curl -sL https://raw.githubusercontent.com/YOUR_USERNAME/vector-memory-openclaw/Calls external URL not in known-safe list
https://github.com/YOUR_USERNAME/vector-memory-openclaw.gitUses known external API (expected, informational)
raw.githubusercontent.comAI Analysis
The skill's primary risk is downloading and executing code from an external GitHub repository (YOUR_USERNAME placeholder) which could be replaced with a malicious source. While no active credential harvesting or data exfiltration is documented, the pattern of fetching external code introduces supply chain risk.
Generated Mar 20, 2026
Enables support agents to quickly find relevant solutions by searching through documentation and past tickets with semantic understanding, automatically falling back to keyword search if vector indexing isn't ready. This reduces resolution time and improves accuracy in handling customer inquiries.
Allows legal professionals to search through case files, contracts, and regulations using semantic queries for concepts like 'liability clauses' or 'intellectual property rights', with automatic fallback to keyword matching. This enhances research efficiency and ensures reliable access even without prior setup.
Helps medical staff retrieve patient histories and treatment notes by understanding medical terminology and synonyms, automatically switching to keyword search if vector sync isn't available. This supports quick decision-making and maintains access during system updates.
Assists educators in finding teaching materials and resources across curricula by semantically matching topics like 'algebraic equations' or 'historical events', with fallback to built-in search for immediate use. This streamlines lesson planning and adapts to varying technical readiness.
Enables developers to search codebases and API docs with semantic understanding of technical terms, automatically using vector search when synced or keyword fallback otherwise. This accelerates debugging and onboarding without requiring configuration.
Offer the vector-memory skill as a cloud-based service with tiered pricing based on usage volume and features like advanced sync options. Revenue is generated through monthly or annual subscriptions from businesses needing scalable memory search solutions.
Sell perpetual licenses to large organizations for on-premises deployment, including customization and support services. Revenue comes from one-time license fees and ongoing maintenance contracts, targeting industries with high data security needs.
Provide a free version with basic memory search capabilities and charge for advanced features like priority sync, larger scale support, or integration with external databases. Revenue is driven by upgrades from individual users to professional tiers.
💬 Integration Tip
Install via ClawHub and use memory_search immediately; run sync optionally for enhanced semantic results without disrupting existing workflows.
Scored Apr 16, 2026
Audited Apr 16, 2026 · audit v1.0
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.
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