Query local documents via AnythingLLM RAG (Retrieval-Augmented Generation). Use when the user asks about their private/local documents, PDFs, uploaded files,...
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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 anythingllm-ragOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install anythingllm-ragβ 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/anythingllm-rag/π‘Extract and place the folder at the path above, then restart your agent.
Category
πDocuments & NotesPlatforms
What anythingllm-rag can do for your AI workflow
Local documents via 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 anythingllm-rag
Help me get started with anythingllm-rag
Explains what anythingllm-rag does, walks through the setup, and runs a quick demo based on your current project
Use anythingllm-rag to query local documents via AnythingLLM RAG (Retrieval-Augmented Gene...
Invokes anythingllm-rag with the right parameters and returns the result directly in the conversation
What can I do with anythingllm-rag in my documents & notes workflow?
Lists the top use cases for anythingllm-rag, with example commands for each scenario
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anythingllm-rag extends your AI assistant with the ability to query local documents via AnythingLLM RAG (Retrieval-Augmented Generation). Use when the user asks about their private/local documents, PDFs, uploaded files,... 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 anythingllm-rag as its underlying capability.
anythingllm-rag 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 anythingllm-rag 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 anythingllm-rag, copy the skill folder to `~/.claude/skills/anythingllm-rag/` for use across all your projects, or `.claude/skills/anythingllm-rag/` for a single project. Restart Claude and the skill is immediately active β invoke it with `/anythingllm-rag` or just describe your goal and the AI will pick it up automatically.
anythingllm-rag has 143 installs and is part of the growing Documents & Notes 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/anythingllm-rag/ for personal use (all projects), or .claude/skills/anythingllm-rag/ for project-specific use. Restart your AI client, then invoke with /anythingllm-rag or let the AI discover it automatically.
anythingllm-rag supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
anythingllm-rag is free to install. Check the repository for licensing information.
Query local documents via AnythingLLM RAG (Retrieval-Augmented Generation). Use when the user asks about their private/local documents, PDFs, uploaded files,...
Automate my documents & notes tasks using anythingllm-rag
Identifies repetitive steps in your workflow and sets up anythingllm-rag to handle them automatically
anythingllm-rag is categorized under Documents & Notes. These skills help AI agents perform specialized tasks in this domain.