Memory layer for AI agents. Local SQLite (free) or Cloud PostgreSQL with BYOK ($10/mo). Knowledge graph, temporal reasoning, multi-hop retrieval.
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install muninn-skillOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install muninn-skillβ 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/muninn-skill/π‘Extract and place the folder at the path above, then restart your agent.
Category
πData & AnalyticsPlatforms
What Muninn Memory can do for your AI workflow
Memory layer for ai agents directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
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 Muninn Memory
Help me get started with Muninn Memory
Explains what Muninn Memory does, walks through the setup, and runs a quick demo based on your current project
Use Muninn Memory to memory layer for AI agents
Invokes Muninn Memory with the right parameters and returns the result directly in the conversation
What can I do with Muninn Memory in my data & analytics workflow?
Lists the top use cases for Muninn Memory, with example commands for each scenario
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Muninn Memory extends your AI assistant with the ability to memory layer for AI agents. Local SQLite (free) or Cloud PostgreSQL with BYOK ($10/mo). Knowledge graph, temporal reasoning, multi-hop retrieval. 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 Muninn Memory as its underlying capability.
Muninn 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 Muninn 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.
To install Muninn Memory, copy the skill folder to `~/.claude/skills/muninn-skill/` for use across all your projects, or `.claude/skills/muninn-skill/` for a single project. Restart Claude and the skill is immediately active β invoke it with `/muninn-skill` or just describe your goal and the AI will pick it up automatically.
Muninn Memory has 73 installs and is part of the growing Data & Analytics skill ecosystem on DiscoverAISkills. 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/muninn-skill/ for personal use (all projects), or .claude/skills/muninn-skill/ for project-specific use. Restart your AI client, then invoke with /muninn-skill or let the AI discover it automatically.
Muninn Memory supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Muninn Memory is free to install. Check the repository for licensing information.
Memory layer for AI agents. Local SQLite (free) or Cloud PostgreSQL with BYOK ($10/mo). Knowledge graph, temporal reasoning, multi-hop retrieval.
Automate my data & analytics tasks using Muninn Memory
Identifies repetitive steps in your workflow and sets up Muninn Memory to handle them automatically
Muninn Memory is categorized under Data & Analytics. 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.