AnythingLLM
Self-hosted RAG chat over your files, 60k+ GitHub stars
Overview
AnythingLLM is an open-source (MIT) workspace for chatting with your own documents — run it locally or in Docker, connect any LLM provider or a local Ollama model, and add multi-user workspaces with role-based access for team use.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 11 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- Full RAG feature set
- Bring your own LLM API key or local model
- MIT open source
- Private instance + custom subdomain
- Under 100 documents
- Bring your own LLM API key
- 72-hour support SLA
- Handles extensive document volumes
- Custom domain and SLA
- Custom integration support
Use cases
What you can produce with AnythingLLM
- MIT-licensed, self-hostable (Docker or one-click desktop app)
- Connects 30+ LLM providers and local models via Ollama/LM Studio
- Multi-user workspaces with role-based access control
- Ingests PDFs, spreadsheets, GitHub repos, audio, and databases
- Built-in agents (web browsing, code execution)
- Acts as an MCP server for Claude Desktop and other MCP clients
ASEAN Perspective
AnythingLLM in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
AnythingLLM is Mintplex Labs' open-source answer to "ChatGPT over my own files" — a desktop app or Docker container that ingests PDFs, spreadsheets, GitHub repos, and more into a private RAG chatbot, with a one-click installer and no account required to run it locally. It connects to 30-plus LLM providers plus local models via Ollama or LM Studio, and now supports MCP servers, so it plugs into the same tool ecosystem as Claude Desktop.
The desktop app and self-hosted Docker version are genuinely free; a managed cloud tier exists for teams that don't want to run their own infrastructure, starting at $50/month. It's a strong pick for developers and privacy-conscious teams who want document QA fully on-premise with no vendor lock-in. Non-technical users will find local-model setup fiddlier than a polished SaaS product, and RAG answer quality depends heavily on which model and embedding settings you choose.
What people say
AnythingLLM comes from Mintplex Labs, a small Y Combinator-backed team led by Timothy Carambat, and its open-source repository — Mintplex-Labs/anything-llm on GitHub, MIT licensed — has crossed 60,000 stars, putting it among the more popular self-hosted AI tools by that measure. Hacker News threads from its early Show HN days praised the single-install desktop packaging as slick compared to the DIY LangChain-plus-vector-database setups most self-hosted RAG projects require.
The feature list is broad for a project this size: connect over 30 LLM providers (OpenAI, Anthropic, local Ollama, and others), pick a vector database (LanceDB is bundled by default, or plug in Pinecone, Qdrant, and others), and ingest PDFs, Word docs, spreadsheets, HTML, audio, GitHub repositories, and database connections. Multi-user workspaces with role-based permissions and built-in agents (web browsing, code execution) round it out, and 2026 reviews specifically flag its Model Context Protocol support as a reason it stays relevant even for people who primarily use Claude Desktop or ChatGPT — you can point those clients at an AnythingLLM instance as an MCP server.
Pricing splits cleanly: the desktop app and self-hosted Docker deployment are free with no account needed, which is the version most reviews focus on. For teams that don't want to run infrastructure, a managed cloud tier starts at $50/month for a private instance handling under 100 documents, $99/month for a Pro tier aimed at larger document sets with a 72-hour support SLA, and custom Enterprise pricing for on-premise installs with dedicated support.
Reviewers who've used it as a daily driver describe it as one of the stronger free alternatives to paying for ChatGPT Plus specifically because you supply your own API key or run a fully local model, so there's no subscription markup on top of raw model costs. The honest caveats: RAG quality is only as good as your chunking and embedding configuration, which takes tuning to get right, and non-technical users will find local-model setup — installing Ollama, pulling a model, wiring up the config — more involved than a polished commercial SaaS tool. It's maintained by a small team rather than a large vendor, so support and roadmap pace depend on community and Mintplex bandwidth rather than an enterprise SLA.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including AnythingLLM's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with AnythingLLM unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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