Built by Mintplex Labs (YC). An MIT-licensed open-source application that combines document chat, RAG, AI agents, Agent Flows, MCP tools, Meeting Assistant, API access, mobile sync, and multi-user workspace management in one deployable unit. Runs as a desktop app (macOS, Windows, Linux), Docker/self-hosted server, hosted cloud instance, or Android-connected mobile app.
System Verdict
Pick AnythingLLM if you need self-hosted document chat, private RAG, or a local-first agent workspace. The MIT license gives you flexibility to modify and deploy. Bring your own LLM tools or custom agent skills, and use Agent Flows when you need repeatable automation rather than one-off chat prompts.
Skip it if you’re a solo user with a single PDF. ChatPDF is one click. If you just need “talk to this one document,” AnythingLLM is over-engineered for the task.
Who pays for cloud: Individuals or small teams (under 5 users, under 100 documents) take Basic at $50/mo for a private hosted instance. Startups and larger teams buy Pro at $99/mo with a 72-hour support SLA. Enterprise (on-premise install, custom SLA, custom domain, custom integration) is by contract. Most technical teams should still compare cloud convenience against the free self-hosted version plus model/API spend.
What Changed Since The Last Refresh
- Pricing is stable, but v1.14.1 moved the product forward. Basic is still $50/month, Pro is still $99/month, and Enterprise is still custom. The important June change is the desktop app reaching v1.14.1, not a plan reshuffle.
- Meeting Assistant is materially stronger. v1.14.1 overhauled Meeting Assistant to be smaller, faster, and more efficient. It adds Intel, AMD, and NVIDIA GPU support, a 92% smaller binary, 15% faster processing, transcription through the Developer API, better context-window overflow handling, basic speaker identification, and dual-channel stereo recording support.
- Agent and workflow surface expanded. Current docs now center AI Agents, custom skills, MCP compatibility, Agent Flows, scheduled jobs, Model Router, Desktop Assistant, Browser Extension, Meeting Assistant, and channels. This is now more than “document chat plus agents.”
- v1.14.0 changed default agent behavior. The changelog says model providers now call tools by default unless you opt out, which should improve agent performance but makes tool governance more important.
- The mobile story is now real. GitHub releases now promote AnythingLLM Mobile on Google Play, syncing with Cloud, self-hosted, and Desktop versions. That changes the page from desktop/server-only to desktop, server, cloud, and mobile-adjacent.
Key Facts
| License | MIT (fully open source) |
| Platforms | Desktop (macOS, Windows, Linux), Docker, cloud |
| Current desktop version | v1.14.1 |
| Self-hosted cost | $0 |
| Cloud tiers | Basic $50/mo (under 5 users, under 100 docs), Pro $99/mo (72-hour support SLA), Enterprise custom (on-prem) |
| LLM support | OpenAI, Anthropic, Google, Ollama (local), Groq, Together, and any OpenAI-compatible endpoint |
| Vector DB support | LanceDB (default), Pinecone, Weaviate, Chroma, Qdrant, and more |
| Document formats | PDF, DOCX, TXT, MD, HTML, CSV, JSON, many more |
| Agent capabilities | Built-in skills, custom skills, MCP tools, Agent Flows, scheduled jobs, Model Router, browser extension, Desktop Assistant |
| Meeting Assistant | v1.14.1 overhaul with smaller binary, faster processing, Developer API transcription, speaker identification, and dual-channel stereo support |
When to pick AnythingLLM
- Regulated industries. Legal, medical, financial, government workflows where documents cannot leave your infrastructure. Self-host + Ollama locally = fully air-gapped.
- Small-to-mid team RAG. Per-seat SaaS pricing gets expensive fast. $50/mo AnythingLLM Cloud Basic covers a team of under 5 cheaper than ChatGPT Team ($30/user) once seat count crosses two.
- Developer RAG prototypes. Open source + extensible = fast iteration. Build your production RAG on top of AnythingLLM’s workspace model.
- Multi-model workflows. Point the same app at OpenAI for deep analysis, Ollama for cheap bulk, and Claude for reasoning tasks. No subscription juggling.
- Teams that want MCP and custom skills without writing a full app. AnythingLLM can add MCP servers, custom agent skills, and Agent Flows inside an existing chat/RAG workspace.
- Meeting-heavy teams that want local or private summaries. v1.14.1 makes Meeting Assistant more credible for teams that need transcription, speaker identification, and longer-meeting summarization without defaulting to another meeting SaaS.
When to pick something else
- Solo casual users: ChatPDF or NotebookLM for occasional document chat. AnythingLLM is a platform; those are focused tools.
- Hands-off SaaS: Humata or ChatPDF if running Docker is not something you want to do.
- with built-in compliance: Glean or similar if you want a vendor-managed enterprise knowledge platform, not self-hosted.
Pricing
| Plan | Price | What’s included |
|---|---|---|
| Self-hosted | $0 | Everything. MIT license. Bring your own LLM + vector DB. |
| Cloud Basic | $50/mo | Private instance, custom subdomain, RAG and agents. Individuals or teams under 5 users with under 100 documents. |
| Cloud Pro | $99/mo | Private instance, RAG and agents, 72-hour support SLA. Startups and larger teams. |
| Enterprise | Custom | On-premise install, custom SLA, custom domain, custom integration. Large companies. |
Prices verified 2026-06-12 via anythingllm.com/cloud.
Failure modes
- Self-hosting has real ops overhead. You manage Docker, updates, vector DB, LLM API keys, backups. If you don’t have ops capacity, pay for cloud or pick a SaaS competitor.
- Setup is not one-click for server deployments. Desktop app is easy; Docker server requires reading docs and configuring environment variables.
- Default LLM is whatever you configure. Quality depends entirely on the backing model. Pair with a strong hosted model from OpenAI, Anthropic Claude, Google Gemini, or a strong local model for good results.
- Community support model. Fewer paid support options than enterprise SaaS competitors. Discord + GitHub issues for most users.
- Vector DB choice affects performance. Default LanceDB is fine for small corpora. For 100k+ documents, switch to Pinecone or Qdrant.
- and tool calling need guardrails. v1.14.0 made tool calling opt-out for model providers. That helps agents, but admins should review which MCP servers, skills, and Agent Flows are enabled.
- Meeting Assistant is not a full meeting-intelligence suite. It is stronger after v1.14.1, but Fireflies, Read AI, and Fathom still win when the whole job is team-wide meeting analytics, CRM sync, coaching, and sales-call review.
Against the alternatives
| AnythingLLM | ChatPDF | NotebookLM | Glean | |
|---|---|---|---|---|
| Open source | Yes (MIT) | No | No | No |
| Self-hosted | Yes | No | No | Enterprise only |
| Multi-document | Yes | Plus only | Yes | Yes |
| Agent framework | Yes | No | No | Limited |
| Pricing model | Free or $50-99/mo | $19.99/mo | Free (gated by Google account) | Enterprise sales |
| Best for | Self-hosted RAG | Quick PDF chat | Google-aligned research | Enterprise search |
Methodology
Produced by the aipedia.wiki editorial pipeline. Last verified 2026-06-18 against anythingllm.com/cloud, the AnythingLLM docs, v1.14.1 release notes, v1.14.0 release notes, MCP compatibility docs, and the GitHub releases page.
FAQ
Is AnythingLLM really free? Yes, under MIT license. Full source on GitHub. You can use, modify, and deploy commercially without restriction. Cloud tiers are optional for teams that don’t want to self-host.
Do I need Docker to run it? Desktop app does not need Docker. Server deployments (for team workspaces) are Docker-based. Docker Compose file is published in the repo.
Which LLM should I use with it? Depends on your workload. Claude or ChatGPT for highest hosted-model quality. Ollama with a capable local model for privacy or cost. Groq for speed. AnythingLLM lets you switch per workspace.
How does it compare to RAG frameworks like LlamaIndex or LangChain? Those are libraries; AnythingLLM is an app. If you’re building a custom RAG pipeline from scratch, use LlamaIndex or LangChain. If you want a working RAG product to configure and use, pick AnythingLLM.
Does AnythingLLM support MCP? Yes. Current docs say AnythingLLM supports MCP tools for use with AI Agents, with configuration paths for Docker and Desktop installs. Treat MCP access as a privileged integration surface because it can connect agents to external tools and data.
What changed in v1.14.1? The headline change is Meeting Assistant. The release also added Linux AppImage size reductions, cached Ollama engine downloads, chat deep links, audio/video uploads through Tinyscribe, chat export to PDF/JSON/Markdown, HD screenshots for Desktop Assistant, and approval hooks for custom skills.
Sources
- AnythingLLM cloud pricing: hosted Basic, Pro, and Enterprise packaging
- AnythingLLM v1.14.1 changelog: Meeting Assistant overhaul, audio/video uploads, chat export, Desktop Assistant, and performance fixes
- AnythingLLM v1.14.0 changelog: Cerebras provider, default tool calling, STT/TTS additions, web-scraping markdown conversion, summary overhaul, and bug fixes
- AnythingLLM MCP compatibility docs: MCP support for AnythingLLM AI Agents
- AnythingLLM GitHub releases: current release and Android mobile availability signal
Related
- Category: AI Chatbots · AI Research
- See also: ChatPDF · NotebookLM · Ollama
