Smart 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.
Data sourced from ClawHub. View on ClawSkills
Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install vector-memoryOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install vector-memoryβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/vector-memory/π‘Extract and place the folder at the path above, then restart your agent.
Category
πDocuments & NotesWhat vector-memory can do for your AI workflow
Smart memory search directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 4,583+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing vector-memory
Help me get started with vector-memory
Explains what vector-memory does, walks through the setup, and runs a quick demo based on your current project
Use vector-memory to smart memory search with automatic vector fallback
Invokes vector-memory with the right parameters and returns the result directly in the conversation
What can I do with vector-memory in my documents & notes workflow?
Lists the top use cases for vector-memory, with example commands for each scenario
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vector-memory extends your AI assistant with the ability to smart 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. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using vector-memory as its underlying capability.
vector-memory works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install vector-memory once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Getting started with vector-memory takes about two minutes. Place the skill at `~/.claude/skills/vector-memory/` (personal, all projects) or `.claude/skills/vector-memory/` (project-specific), then restart your AI client. From that point, typing `/vector-memory` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.
vector-memory has been installed 4,583 times, making it one of the more actively used skills in the Documents & Notes category. The install rate suggests it solves a real, recurring need rather than a niche edge case. The source code is open on GitHub β you can inspect it, contribute fixes, or fork it to adapt the skill for your specific setup. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/vector-memory/ for personal use (all projects), or .claude/skills/vector-memory/ for project-specific use. Restart your AI client, then invoke with /vector-memory or let the AI discover it automatically.
vector-memory supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
vector-memory is free to install. Check the repository for licensing information.
Smart 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.
Platforms
Links
Automate my documents & notes tasks using vector-memory
Identifies repetitive steps in your workflow and sets up vector-memory to handle them automatically
vector-memory is categorized under Documents & Notes. These skills help AI agents perform specialized tasks in this domain.
Local memory management for agents. Compression detection, auto-snapshots, and semantic search. Use when agents need to detect compression risk before memory loss, save context snapshots, search historical memories, or track memory usage patterns. Never lose context again.