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anything-llm

starFeaturedMCP Server

The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility...

Copy the install, test the workflow, then decide if it earns a permanent slot.

56,049
Why nowMoving now

Fresh repo activity plus visible builder pull. This is the kind of tool people test before it turns obvious.

DecisionHigh-conviction move

Copy the install, test the workflow, then decide if it earns a permanent slot.

Trial costMedium lift

Testable in one sitting, but you will likely touch real infra or local setup before you know if it sticks.

Risk39/100

GitHub health 87/100. no security policy. 348 open issues make this testable, but not something to trust blind.

What You Are Adopting

AI Agent

Multiple

Model

Multiple

Build Time

Days

Test This In Your Stack

One command inClean rollbackLow commitment
settingsRegistryAdds a named entry to Claude config. One command to remove.

Fastest way to find out if anything-llm belongs in your setup.

Copy the install command, run a real test, and back it out cleanly if it slows you down.

Try now
claude mcp add anything-llm -- npx anything-llm

Run this first. You will know quickly if the workflow earns a permanent slot.

Back out
claude mcp remove anything-llm

No messy cleanup loop. If it misses, remove it and keep moving.

Install Location

~/  └─ .claude.json    └─ mcp_servers/      └─ anything-llm ← registers here

About

The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.. An open-source mcp server for the AI coding ecosystem.

README

AnythingLLM logo

Mintplex-Labs%2Fanything-llm | Trendshift

AnythingLLM: 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.

Discord | License | Docs | Hosted Instance

English · 简体中文 · 日本語

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

A full-stack application that enables you to turn any document, resource, or piece of content into context that any LLM can use as a reference during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions.

Chatting

Watch the demo!

Watch the video

Product Overview

AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open source LLMs and vectorDB solutions to build a private ChatGPT with no compromises that you can run locally as well as host remotely and be able to chat intelligently with any documents you provide it.

AnythingLLM divides your documents into objects called workspaces. A Workspace functions a lot like a thread, but with the addition of containerization of your documents. Workspaces can share documents, but they do not talk to each other so you can keep your context for each workspace clean.

Cool features of AnythingLLM

  • 🆕 Full MCP-compatibility
  • 🆕 No-code AI Agent builder
  • 🖼️ Multi-modal support (both closed and open-source LLMs!)
  • Custom AI Agents
  • 👤 Multi-user instance support and permissioning Docker version only
  • 🦾 Agents inside your workspace (browse the web, etc)
  • 💬 Custom Embeddable Chat widget for your website Docker version only
  • 📖 Multiple document type support (PDF, TXT, DOCX, etc)
  • Simple chat UI with Drag-n-Drop functionality and clear citations.
  • 100% Cloud deployment ready.
  • Works with all popular closed and open-source LLM providers.
  • Built-in cost & time-saving measures for managing very large documents compared to any other chat UI.
  • Full Developer API for custom integrations!
  • Much more...install and find out!

Supported LLMs, Embedder Models, Speech models, and Vector Databases

Large Language Models (LLMs):

  • Any open-source llama.cpp compatible model
  • OpenAI
  • OpenAI (Generic)
  • Azure OpenAI
  • AWS Bedrock
  • Anthropic
  • NVIDIA NIM (chat models)
  • Google Gemini Pro
  • Hugging Face (chat models)
  • Ollama (chat models)
  • LM Studio (all models)
  • LocalAI (all models)
  • Together AI (chat models)
  • Fireworks AI (chat models)
  • Perplexity (chat models)
  • OpenRouter (chat models)
  • DeepSeek (chat models)
  • Mistral
  • Groq
  • Cohere
  • KoboldCPP
  • LiteLLM
  • Text Generation Web UI
  • Apipie
  • xAI
  • Z.AI (chat models)
  • Novita AI (chat models)
  • PPIO
  • Gitee AI
  • Moonshot AI
  • Microsoft Foundry Local
  • CometAPI (chat models)
  • Docker Model Runner
  • PrivateModeAI (chat models)
  • SambaNova Cloud (chat models)
  • Lemonade by AMD

Embedder models:

  • AnythingLLM Native Embedder (default)
  • OpenAI
  • Azure OpenAI
  • LocalAI (all)
  • Ollama (all)
  • LM Studio (all)
  • Cohere

Audio Transcription models:

  • AnythingLLM Built-in (default)
  • OpenAI

TTS (text-to-speech) support:

  • Native Browser Built-in (default)
  • PiperTTSLocal - runs in browser
  • OpenAI TTS
  • ElevenLabs
  • Any OpenAI Compatible TTS service.

STT (speech-to-text) support:

  • Native Browser Built-in (default)

Vector Databases:

  • LanceDB (default)
  • PGVector
  • Astra DB
  • Pinecone
  • Chroma & ChromaCloud
  • Weaviate
  • Qdrant
  • Milvus
  • Zilliz

Technical Overview

This monorepo consists of six main sections:

  • frontend: A viteJS + React frontend that you can run to easily create and manage all your content the LLM can use.
  • server: A NodeJS express server to handle all the interactions and do all the vectorDB management and LLM interactions.
  • collector: NodeJS express server that processes and parses documents from the UI.
  • docker: Docker instructions and build process + information for building from source.
  • embed: Submodule for generation & creation of the web embed widget.
  • browser-extension: Submodule for the chrome browser extension.

🛳 Self-Hosting

Mintplex Labs & the community maintain a number of deployment methods, scripts, and templates that you can use to run AnythingLLM locally. Refer to the table below to read how to deploy on your preferred environment or to automatically deploy.

Docker AWS GCP Digital Ocean Render.com
Deploy on Docker Deploy on AWS Deploy on GCP Deploy on DigitalOcean Deploy on Render.com
Railway RepoCloud Elestio Northflank
Deploy on Railway Deploy on RepoCloud Deploy on Elestio Deploy on Northflank

or set up a production AnythingLLM instance without Docker →

How to setup for development

  • yarn setup To fill in the required .env files you'll need in each of the application sections (from root of repo).
    • Go fill those out before proceeding. Ensure server/.env.development is filled or else things won't work right.
  • yarn dev:server To boot the server locally (from root of repo).
  • yarn dev:frontend To boot the frontend locally (from root of repo).
  • yarn dev:collector To then run the document collector (from root of repo).

Learn about documents

Learn about vector caching

External Apps & Integrations

These are apps that are not maintained by Mintplex Labs, but are compatible with AnythingLLM. A listing here is not an endorsement.

  • Midori AI Subsystem Manager - A streamlined and efficient way to deploy AI systems using Docker container technology.
  • Coolify - Deploy AnythingLLM with a single click.
  • GPTLocalhost for Microsoft Word - A local Word Add-in for you to use AnythingLLM in Microsoft Word.

Telemetry & Privacy

AnythingLLM by Mintplex Labs Inc contains a telemetry feature that collects anonymous usage information.

More about Telemetry & Privacy for AnythingLLM

Why?

We use this information to help us understand how AnythingLLM is used, to help us prioritize work on new features and bug fixes, and to help us improve AnythingLLM's performance and stability.

Opting out

Set DISABLE_TELEMETRY in your server or docker .env settings to "true" to opt out of telemetry. You can also do this in-app by going to the sidebar > Privacy and disabling telemetry.

What do you explicitly track?

We will only track usage details that help us make product and roadmap decisions, specifically:

  • Type of your installation (Docker or Desktop)

  • When a document is added or removed. No information about the document. Just that the event occurred. This gives us an idea of use.

  • Type of vector database in use. This helps us prioritize changes when updates arrive for that provider.

  • Type of LLM provider & model tag in use. This helps us prioritize changes when updates arrive for that provider or model, or combination thereof. eg: reasoning vs regular, multi-modal models, etc.

  • When a chat is sent. This is the most regular "event" and gives us an idea of the daily-activity of this project across all installations. Again, only the event is sent - we have no information on the nature or content of the chat itself.

You can verify these claims by finding all locations Telemetry.sendTelemetry is called. Additionally these events are written to the output log so you can also see the specific data which was sent - if enabled. No IP or other identifying information is collected. The Telemetry provider is PostHog - an open-source telemetry collection service.

We take privacy very seriously, and we hope you understand that we want to learn how our tool is used, without using annoying popup surveys, so we can build something worth using. The anonymous data is never shared with third parties, ever.

[View all telemetry events in source code](https://github.com/search?q=repo%3AMintplex-Labs%2Fanything-llm%20.sendTelemetry(&type=code)

👋 Contributing

  • Contributing to AnythingLLM - How to contribute to AnythingLLM.

💖 Sponsors

Premium Sponsors

User avatar: DCS DIGITAL

All Sponsors

User avatar: JaschaUser avatar: KickAssUser avatar: ShadowArcanistUser avatar: AtlasUser avatar: Predrag StojadinovićUser avatar: Diego SpinolaUser avatar: KyleUser avatar: Giulio De PasqualeUser avatar: User avatar: MacStadiumUser avatar: User avatar: User avatar: User avatar: User avatar: DennisUser avatar: Michael Hamilton, Ph.D.User avatar: User avatar: TernaryLabsUser avatar: Daniel CelaUser avatar: AlessoUser avatar: Rune MathisenUser avatar: User avatar: User avatar: AlanUser avatar: Damien PetersUser avatar: DCS DigitalUser avatar: Paul McilreavyUser avatar: Til WolfUser avatar: Leopoldo Crhistian Riverin GomezUser avatar: AJEsauUser avatar: Steven VanOmmerenUser avatar: Casey BoettcherUser avatar: User avatar: AvineetUser avatar: ChrisUser avatar: mirkoUser avatar: Tim ChampUser avatar: Peter MathisenUser avatar: Ed di GirolamoUser avatar: Wojciech MiłkowskiUser avatar: ADS FundUser avatar: arc46 GmbHUser avatar: Li YinUser avatar: SylphAI

🌟 Contributors

anythingllm contributors

Star History Chart

🔗 More Products

  • VectorAdmin: An all-in-one GUI & tool-suite for managing vector databases.
  • OpenAI Assistant Swarm: Turn your entire library of OpenAI assistants into one single army commanded from a single agent.


Copyright © 2026 Mintplex Labs.
This project is MIT licensed.

Tech Stack

GoLLMDockerAWSReactExpressViteOpenAIAnthropicHugging FaceOllama

Installation

yarn setup

.env

server/.env.development

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ActiveLast commit today
bug_report348open issues
Submitted June 4, 2023

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