Compare LangBot
Side-by-side comparisons to help you decide how to run AI bots in chat apps: deployment options, using LangBot with Dify, n8n or Coze, and how LangBot differs from other bot platforms.
What LangBot gives you out of the box
No deployment: cloud.langbot.app
Sign up and build a bot in your browser. Free plan, public URL included.
cloud.langbot.app- Sign up
- Pick a platform
- Bot online
Details ›
Sign up at cloud.langbot.app and build a bot in the browser with a setup wizard. There is a free plan, the public HTTPS URL webhook platforms need is included, and a Dedicated environment is available for production. Self-hosting stays free and unlimited.
Official model service: LangBot Models
Top models ready to use. No API key to apply for.
- Claude
- GPT
- Gemini
- DeepSeek
- Qwen
- GLM
- Kimi
- Grok
No API key neededDetails ›
Claude, GPT, Gemini, DeepSeek, Qwen, GLM, Kimi, Grok and more, plus embedding, rerank and speech models, with no model API key to obtain. Cloud plans include monthly credits; self-hosted instances signed in with a LangBot Space account get the models added automatically with a free starter quota. Your own API keys keep working alongside.
Control your bots in natural language
Say what should change. Agents and the assistant carry it out after you approve.
In the support group, only answer when someone @mentions the bot, and welcome new members.Routing: reply on @mentiongroup.member_joined → welcomeApplied after you confirmDetails ›
Agents, a unified API and standard platform events and APIs work together. Every Workspace operation (bots, routing, pipelines, models, knowledge bases, monitoring) is one catalog shared by the HTTP API, the MCP server, the Workspace Assistant and plugins, and adapters expose standard platform APIs such as send, reply, edit and recall messages, query groups and members, and, where the platform allows, mute or remove members. So you can change how a bot behaves by telling the Workspace Assistant, or let an authorized agent act on the platform from a chat instruction. Writes need your confirmation or an explicit permission grant.
Workspace Assistant
Describe the goal; review the proposed changes; confirm.
Proposed changes
- Create pipeline “Support”
- Attach knowledge base “FAQ”
- Bind to the WeCom bot
ConfirmDetails ›
Describe what you want in plain language. The assistant inspects your existing models, knowledge bases and pipelines, proposes a configuration and applies it only after you confirm each change.
Rich APIs and flexible tools
One set of operations behind HTTP, MCP, CLI and webhooks; agents get MCP, Skills, a sandbox and knowledge bases.
One Workspace API
HTTP APIMCP ServerlbctlWebhooksAgent tools
MCPSkillsSandboxRAGEventsDetails ›
An HTTP Service API with API keys, LangBot's own MCP server, the
lbctlCLI and outgoing event webhooks for your systems. Agents can use MCP tools (stdio and HTTP), Skills, a code sandbox (Docker, nsjail or E2B), knowledge bases with rerank, and platform events such as member joins, reactions and card clicks.Rich, stable plugin interfaces
Seven component types in an isolated runtime, with permissions you grant.
Plugin Runtime · isolated process
RunnerToolCommandEventListenerKnowledgeEngineParserPageCertified PluginsDetails ›
Plugins run in a separate Plugin Runtime process and are hot-pluggable. The Python SDK offers Runner, Tool, Command, EventListener, KnowledgeEngine, Parser and Page components, and a Workspace API whose operations a plugin must declare and a member must grant. The LangBot Space marketplace lists plugins, MCP servers and Skills, with reviewed Certified Plugins.
Open source, with official backing
Apache 2.0, official hosting and enterprise support.
Apache 2.0Free commercial useOfficial CloudEnterprise SupportDetails ›
Apache 2.0 with free commercial use, an official managed service, and optional Enterprise Support with contracts and invoices.
Choosing a setup
- Self-hosted LangBot vs LangBot CloudCompare running open-source LangBot on your own server with LangBot Cloud: start instantly at cloud.langbot.app with no deployment, or choose a Dedicated environment for production.
- Dify on its own vs Dify + LangBotDify builds the AI app; LangBot delivers it to chat platforms. Compare Dify's own publishing options with running a Dify app through LangBot on Discord, Telegram, Slack, WeCom, Lark, DingTalk and QQ.
- n8n chat nodes vs n8n + LangBotBuild chatbots directly with n8n's chat and messaging nodes, or let LangBot handle the chat platforms and call one n8n workflow. Compare effort, platforms and group-chat handling.
- Coze publishing vs Coze + LangBotCoze can publish agents to its own list of channels. Compare that with calling a Coze agent through LangBot to reach Discord, Telegram, Slack, WeCom, Lark, DingTalk, QQ and more from one place.
- LangBot vs building your own botShould you write your own Slack/Telegram/WeCom bot around an LLM API, or use LangBot? Compare the work involved: adapters, sessions, streaming, group chats, knowledge bases, monitoring and upgrades.
LangBot and other platforms
- LangBot vs OpenClawOpenClaw is a personal AI assistant that runs on your own computer. LangBot runs AI agents that serve a team's customers and members in chat apps. Compare purpose, users, platforms and deployment.
- LangBot vs BotpressCompare LangBot, an open-source AI bot platform you can self-host, with Botpress Cloud, a hosted bot builder: deployment, channels, Chinese IM support, AI back ends and licensing.
- LangBot vs NoneBot and KoishiNoneBot (Python) and Koishi (TypeScript) are general chatbot frameworks for developers. LangBot is an AI-native bot platform with a web panel, built-in Agent, knowledge bases and Dify/n8n/Coze integration. Compare them.
- LangBot vs AstrBotLangBot and AstrBot are both open-source AI chatbot platforms for IM apps. Compare licensing, managed hosting, team features, platforms and agent-platform integration.