7 Open WebUI Alternatives in 2026, Compared Honestly (Us Included)

You are looking for an Open WebUI alternative because the configuration has become too much, because you want to connect MCP servers without a detour, or because you need agents that do more than talk and can actually touch files. The short answer, before the table:

• Several users, many model providers, MCP, your own server: LibreChat.
• Querying documents (RAG) with little setup, also as a desktop app: AnythingLLM.
• Polished interface, plugin catalog, a stage for assistants: LobeChat.
• Local only, one machine, no cloud: Jan (open source) or Msty (proprietary, more convenient).
• Searching company knowledge in Confluence, Slack, Drive: Onyx.
• Agents with editor, Git and terminal in the browser, hosted in Nuremberg, keys redacted before sending: UltraNOS, which is us. Not open source, and that is spelled out below without hedging.

And yes: for plain chat with Ollama and a few friends, Open WebUI is often still the right choice. More on that at the end.

The Criteria and How the Seven Tools Score

The comparison follows what the Reddit threads on "open webui alternative" actually ask about: MCP support, agents with tools, editor and terminal, hosting location, and the effort needed to get to a first chat. The details on third-party tools come from their own documentation, as of September 2026. Where I am not sure about a license or a feature, it says "see repo" instead of a claim.

Tool	License	MCP	Agents	Editor / terminal	Hosting	Effort
Open WebUI	custom license with a branding clause (see repo)	via mcpo proxy, native according to docs (see docs)	Tools/Functions, Pipelines	no / no	self-hosted	medium to high
LibreChat	MIT (see repo)	yes, in librechat.yaml	Agents, Code Interpreter (paid service)	no / no	self-hosted	medium
AnythingLLM	MIT (see repo)	yes	Agents with skills	no / no	self-hosted or desktop	low
LobeChat	see repo	yes, plugin catalog	Assistants, plugins	no / no	self-hosted or the vendor's cloud	medium
Jan	see repo (copyleft)	yes, experimental according to docs	Assistants	no / no	local machine	low
Msty	proprietary	in Msty Studio (see docs)	Tools in Studio	no / no	local machine	low
Onyx	MIT, enterprise folder separate (see repo)	yes	Assistants with tools	no / no	self-hosted or the vendor's cloud	high
UltraNOS	proprietary, private repo	connect your own MCP servers, registry in the backend	Agent fleet, sub-agents, pipeline	Monaco / PTY in the browser	Nuremberg, self-hosting on request	none (create an account)

Two things stand out. First, nobody but us has an editor and terminal, because all the others are built as chat interfaces and want to stay that way. Second, "hosting location" for open-source tools always means "wherever you run it". Where your prompts go is still decided by the model provider you enter. That holds for all eight rows, ours included.

LibreChat

LibreChat is the most obvious alternative if Open WebUI has become too opinionated for you. The project is MIT-licensed (see repo) and ships multi-user login, conversation branching and a long list of providers: OpenAI, Anthropic, Google, Azure, Bedrock, Ollama and anything that speaks the OpenAI API. You register MCP servers in librechat.yaml, and agents get tools, files and instructions.

Strength: the breadth of providers, and the fact that configuration lives in a single file rather than in scattered admin dialogs. If you can read YAML, you find your way around quickly.

Weakness: the Docker Compose file pulls in MongoDB, Meilisearch and a RAG service. That is more infrastructure than Open WebUI with its single SQLite file. The Code Interpreter is a paid API service run by the project, not part of self-hosting. There is no terminal and no editor.

Who it is for: teams that want one chat interface for many models with clean user management and already run a server.

AnythingLLM

AnythingLLM from Mintplex Labs is built around one thing: put documents into "workspaces" and talk to them. MIT license (see repo). There is a desktop app for Mac, Windows and Linux and a Docker image for the server; the server version supports multiple users. Agents with skills and MCP servers are included according to the docs.

Strength: the path from an empty screen to a first RAG chat is short. Model provider, embedding model and vector database are chosen in the setup dialog, no config file needed.

Weakness: if you want more than RAG, you hit the limits of the concept. The agents are designed for web search, documents and a few skills, not for software development. Details such as prompt templates or model routing are simpler than in Open WebUI.

Who it is for: individuals and small teams who mainly want to query their own documents and have no appetite for Docker Compose tinkering.

LobeChat

LobeChat is the interface with the strongest design ambition on this list. It has a plugin catalog, a marketplace for assistants and MCP support; the vendor offers its own cloud version. Self-hosted, it runs either in a light mode (data in the browser) or in server mode with PostgreSQL and login. For the license, please check the repo; it has been changed in the past.

Strength: looks and plugin ecosystem. If people without a technical background are going to use the interface, LobeChat is the friendliest of the seven.

Weakness: server mode needs PostgreSQL, S3-compatible storage for files and an auth provider. That is a similar number of moving parts as with LibreChat, just less visibly documented. Tools for developers are missing.

Who it is for: anyone who wants a ChatGPT-like interface for many users and values appearance and plugins.

Jan

Jan is not server software but a desktop app that runs models locally via llama.cpp and also allows cloud providers. The license is copyleft (see repo for details). Jan provides a local OpenAI-compatible server, so other tools on the same machine can use the models too. MCP support is included according to the docs, but marked as experimental.

Strength: nothing leaves the machine as long as you do not enter a cloud model. Installation is a double-click, and models are downloaded from the hub.

Weakness: no multi-user, no access from a phone or over the network, no hosting. If you use Open WebUI for its web interface for several people, you will not find a replacement here.

Who it is for: individuals with a decent GPU who want to run local models without a server.

Msty

Msty plays in the same category as Jan but is proprietary. The desktop app connects local and remote models, can run several models side by side in split chats and includes "Knowledge Stacks" for RAG. For tools and MCP, the vendor points to Msty Studio; which features there are paid is listed on the vendor's pricing page and changes, so please read it there.

Strength: the most convenient setup on the whole list. Msty is built so that you are chatting after two minutes, even if you have never opened a terminal.

Weakness: no source code, no server version, no multi-user management. Whether and how telemetry is collected is answered only by the vendor's privacy policy.

Who it is for: individual users for whom convenience matters more than insight into the code.

Onyx

Onyx, formerly Danswer, is less a chat interface than company search with a chat in front. The community edition is MIT-licensed, the enterprise folder is under its own license (see repo). Connectors pull content from Confluence, Google Drive, Slack, GitHub, Jira and other sources into an index; assistants answer questions over it, with tools and MCP support according to the docs.

Strength: exactly what Open WebUI's document feature only gets partway to. Permissions per source, connector refresh, search across everything.

Weakness: it is hard to run. The stack includes several services plus a search index; the docs state the memory and core requirements, and they are well above a single Open WebUI container. For a two-person setup, that is too much machine.

Who it is for: companies of a few dozen people or more whose problem is scattered knowledge, not a missing chat interface.

UltraNOS, Placed Honestly

UltraNOS is the tool I build myself, so read this section with the appropriate distance.

What it is: an AI workspace in the browser where the chat sits next to a Monaco editor, a Git panel and a real terminal (PTY over WebSocket). Agents run as background tasks following the pattern think, act, check, with round limits, error limits and a loop guard that no longer executes the fifth identical tool call with an identical result. From the chat you can start sub-agents, up to 16 at the same time, and watch and stop them in a fleet. You register your own MCP servers in the settings and the backend pools them; providers are Claude (API or as your own Claude Code instance), OpenAI-compatible endpoints and Ollama, distributed via model routing with eight slots.

The real difference from the other six is the redaction: the cloak module replaces API keys, passwords in command lines and email addresses with placeholders before the request reaches the model provider, and puts them back into the response. It is pattern-based with 49 replacing rules. That also means a secret with no recognizable prefix, no assignment and low entropy gets through. And on the Claude Code path, only the prompt and system prompt are masked, not the tool results that the CLI generates itself. Both points are stated that way in our documentation, and the status is available via GET /api/health in the cloak field.

What UltraNOS is not: open source. The repo is private. The service is hosted at Hetzner in Nuremberg, a data processing agreement is available; self-hosting is available on request, not as a download. Plans: Starter €0, Pro €19/month, Team €49/month, each with a 14-day trial. There is an Android app and an installable PWA, see Downloads, but no desktop app and no model of its own.

Who it is for: developers who want agents with a terminal and Git without maintaining a server themselves, and who need a verifiable answer to the question "what happens to my key in the prompt". If you want to run the tool yourself, the honest calculation is in the post Self-hosting AI agents.

Decision Tree

1. Should it run on a single machine only, without a server? Open source: Jan. Convenient and proprietary: Msty. Otherwise continue.
2. Is company knowledge across many sources your core problem? Onyx, knowing that running it takes work. Otherwise continue.
3. Do you need an editor, Git and terminal next to the agent? UltraNOS, if hosting in Nuremberg works for you. If it must be open source and self-run, there is no match on this list; then an editor with an agent plus a separate chat interface is the realistic combination. Otherwise continue.
4. Mainly querying documents? AnythingLLM. Otherwise continue.
5. Many users, many providers, MCP in one configuration file? LibreChat. If looks matter more than provider breadth: LobeChat.

Who Should Still Use Open WebUI

The charge from the Reddit threads is "configuring it is a nightmare". That applies to the moment you want to combine pipelines, filter functions and tool servers. It does not apply to the basic case: one container, Ollama next to it, login, done. Open WebUI has the largest community of the seven, the docs at docs.openwebui.com are extensive, and MCP servers can be connected as OpenAPI services via the mcpo proxy; whether your version already speaks MCP natively is shown on the docs' versions page. Watch the license: since 2025 a custom license with a branding clause applies, and the details are in the repo. If you use Open WebUI in the basic case and it works, there is no reason to switch.

FAQ

Which Open WebUI alternative supports MCP without a proxy?

LibreChat, AnythingLLM, LobeChat and Onyx list MCP servers in their docs as directly configurable; Jan lists it as experimental. With Open WebUI, the classic route is the mcpo proxy, which exposes MCP servers as OpenAPI services. UltraNOS maintains a list of your own MCP servers in the backend and bundles them with the local memory and skill services.

LibreChat or Open WebUI?

LibreChat if you want to manage many providers in one YAML file and multi-user operation with MongoDB does not bother you. Open WebUI if you mainly run Ollama, prefer a single file as the database and see the large community as an asset. Neither ships an editor or a terminal.

Is there a self-hosted ChatGPT alternative that also runs code?

Within the chat interfaces only to a limited extent: LibreChat offers a Code Interpreter as a paid service, and Open WebUI can run Python in the browser via Pyodide. A real terminal with file access, Git and processes exists on this list only in UltraNOS, which is hosted though and offers self-hosting only on request.

Do my prompts go to third parties with these tools?

That depends not on the tool but on the model you enter. With Ollama or Jan locally, everything stays on your machine. With OpenAI, Anthropic or another API provider, prompts go there, no matter which interface sits in front. UltraNOS redacts keys and addresses before sending, but cannot change the fact that the text goes to the chosen provider.

Who This Is Not For

If open source is a hard requirement, UltraNOS is out, and so is Msty. If your setup is a Raspberry Pi with Ollama and three users, Open WebUI serves you well and you do not need this comparison. And if you want company search with permission management, none of the chat interfaces is the answer, but Onyx is, with everything its operation costs. The table above is a snapshot from September 2026; the projects move fast, and a look at their changelogs before deciding never hurts.

Your keys stay yours — the rest runs in the browser.

UltraNOS is the agentic web IDE: parallel AI agents, editor, git and terminal. cloak replaces API keys and passwords before a prompt reaches the provider. Hosted in Germany, 14 days free.

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