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anything-llm

Mintplex-Labs/anything-llm · Updated

Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience

Mintplex-Labs/anything-llm is a JavaScript repository in the RAG & Retrieval category with 67,699 stars and 7,614 forks on GitHub, released under the MIT license, last updated today.

#agent-computer#agent-harness#agent-orchestration#agentic-ai#agentic-workflow#ai-agents#computer-use#hermes-agent
View on GitHub 68kGitHub stars

How to install anything-llm in your AI client

Setup for Claude Code, Claude Desktop, Cursor, Codex, Windsurf, Cline and VS Code — copy-paste ready.

How to install anything-llm in Claude CodeAnthropic's agentic CLI

  1. Clone & open

    bash
    git clone https://github.com/Mintplex-Labs/anything-llm.git
cd anything-llm
claude

  2. Let Claude read it

    Ask “/init” to generate a CLAUDE.md, then have Claude explain, run, or extend the codebase. It reads files on demand.

Documentation

Full README

<b>AnythingLLM:</b> The all-in-one AI app you were looking for. Chat with your docs, use AI Agents, hyper-configurable, multi-user, & no frustrating setup required.

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Docs |

Hosted Instance

<b>English</b> · 简体中文 · 日本語

👉 AnythingLLM for desktop (Mac, Windows, & Linux)! Download Now

📱 AnythingLLM Mobile (Android) is open source! View the repo

Chat with your docs. Automate complex workflows with AI Agents. Hyper-configurable, multi-user ready, battle-tested—and runs locally by default with zero setup friction.

<details> <summary><kbd>Watch the demo!</kbd></summary>

</details>

Product Overview

AnythingLLM is the all-in-one AI application that lets you build a private, fully-featured ChatGPT—without compromises. Connect your favorite local or cloud LLM, ingest your documents, and start chatting in minutes. Out of the box you get built-in agents, multi-user support, vector databases, and document pipelines — no extra configuration required.

AnythingLLM supports multiple users as well where you can control the access and experience per user without compromising the security or privacy of the instance or your intellectual property.

Excerpt — the full document is on GitHub.

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