Persistent semantic memory layer for AI agents. Local-first storage (SQLite+LanceDB) with Ollama embeddings. Store and recall facts, decisions, preferences, events, relationships across sessions. Supports memory decay, deduplication, typed memories (5 types), memory relationships (7 graph relation types), agent/user scoping, semantic search, context-aware recall, auto-extraction from text (rules/LLM/hybrid), import/export, REST API, MCP protocol. Solves context window and compaction amnesia. Server at localhost:3400, dashboard at /dashboard. Install via npm (engram-memory), requires Ollama with nomic-embed-text model.
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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 engramOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install engramβ 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/engram/π‘Extract and place the folder at the path above, then restart your agent.
Category
Data & AnalyticsWhat Engram can do for your AI workflow
Persistent semantic memory directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 1,821+ 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 Engram
Help me get started with Engram
Explains what Engram does, walks through the setup, and runs a quick demo based on your current project
Use Engram to persistent semantic memory layer for AI agents
Invokes Engram with the right parameters and returns the result directly in the conversation
What can I do with Engram in my data & analytics workflow?
Lists the top use cases for Engram, with example commands for each scenario
Guides & tutorials for AI skills
Engram extends your AI assistant with the ability to persistent semantic memory layer for AI agents. Local-first storage (SQLite+LanceDB) with Ollama embeddings. Store and recall facts, decisions, preferences, events, relationships across sessions. Supports memory decay, deduplication, typed memories (5 types), memory relationships (7 graph relation types), agent/user scoping, semantic search, context-aware recall, auto-extraction from text (rules/LLM/hybrid), import/export, REST API, MCP protocol. Solves context window and compaction amnesia. Server at localhost:3400, dashboard at /dashboard. Install via npm (engram-memory), requires Ollama with nomic-embed-text model. 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 Engram as its underlying capability.
Engram 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 Engram 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 Engram, copy the skill folder to `~/.claude/skills/engram/` for use across all your projects, or `.claude/skills/engram/` for a single project. Restart Claude and the skill is immediately active β invoke it with `/engram` or just describe your goal and the AI will pick it up automatically.
Engram has been installed 1,821 times, making it one of the more actively used skills in the Data & Analytics category. The install rate suggests it solves a real, recurring need rather than a niche edge case. 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/engram/ for personal use (all projects), or .claude/skills/engram/ for project-specific use. Restart your AI client, then invoke with /engram or let the AI discover it automatically.
Engram supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Engram is free to install. Check the repository for licensing information.
Persistent semantic memory layer for AI agents. Local-first storage (SQLite+LanceDB) with Ollama embeddings. Store and recall facts, decisions, preferences, events, relationships across sessions. Supports memory decay, deduplication, typed memories (5 types), memory relationships (7 graph relation types), agent/user scoping, semantic search, context-aware recall, auto-extraction from text (rules/LLM/hybrid), import/export, REST API, MCP protocol. Solves context window and compaction amnesia. Server at localhost:3400, dashboard at /dashboard. Install via npm (engram-memory), requires Ollama with nomic-embed-text model.
Automate my data & analytics tasks using Engram
Identifies repetitive steps in your workflow and sets up Engram to handle them automatically
MCP vs traditional plugins: what's the difference?
Engram is categorized under Data & Analytics. These skills help AI agents perform specialized tasks in this domain.