langbot

What is LangBot?

LangBot is an open-source, production-grade platform for building AI-powered instant messaging bots. It connects Large Language Models (LLMs) to any chat platform, enabling you to create intelligent agents that can converse, execute tasks, and integrate with your existing workflows.

Key Capabilities

• AI Conversations & Agents — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to Dify, Coze, n8n, Langflow, Deerflow, Weknora.
• Universal IM Platform Support — One codebase for Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
• Production-Ready — Access control, rate limiting, sensitive word filtering, comprehensive monitoring, and exception handling. Trusted by enterprises.
• Plugin Ecosystem — Hundreds of plugins, event-driven architecture, component extensions, and MCP protocol support.
• Web Management Panel — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
• Multi-Pipeline Architecture — Different bots for different scenarios, with comprehensive monitoring and exception handling.

→ Learn more about all features

📍 Practical guides: deploy a multi-platform AI bot in 5 minutes, connect DeepSeek to WeChat, Discord, and Telegram, run a Dify Agent in Discord, Telegram, and Slack, and build an n8n-powered chatbot.

😎 Stay Updated

Click the Star and Watch buttons in the top-right corner of the repository to get the latest updates.

Quick Start

☁️ LangBot Cloud (Recommended)

**LangBot Cloud** — Zero deployment, ready to use.

One-Line Launch

uvx langbot

> Requires uv. Visit http://localhost:5300 — done.

Docker Compose

git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose --profile all up -d

One-Click Cloud Deploy

More options: Docker · Manual · BTPanel · Kubernetes

Live Demo

Try it now: https://demo.langbot.dev/

• Email: `demo@langbot.app`
• Password: `langbot123456`

_Note: Public demo environment. Do not enter sensitive information._

Supported Platforms

Supported LLMs & Integrations

→ View all integrations

Why LangBot?

Built for AI Agents 🤖

LangBot is agent-friendly by design — your coding agents (Claude Code, Codex, Copilot, Cursor, …) can operate, extend, and deploy LangBot with first-class support:

• MCP Server — LangBot exposes a built-in Model Context Protocol endpoint at `/mcp`, mirroring the HTTP API so an agent can manage bots, pipelines, plugins, and models programmatically. Authenticate with the same API key (set a global key in `config.yaml` or use a per-user key) — no login flow required. Configure it in the Web panel's API & MCP tab.
• In-repo Skills — The `skills/` directory is the single source of truth for working with LangBot: plugin development, core development, end-to-end testing, deployment, and operating the LangBot / LangBot Space MCP servers. Point your agent at this directory and it knows how to build.
• AGENTS.md — Every repo ships an `AGENTS.md` (symlinked to `CLAUDE.md`) describing architecture, conventions, and the rule that API changes must keep the MCP server and skills in sync.
• `llms.txt` — Machine-readable project context for LLMs is published on the website.

> Cloud / Marketplace: LangBot Space also exposes an MCP server so agents can search and inspect the plugin / MCP / skill marketplace, authenticated with a Personal Access Token.

Community

• Discord Community

Contributors

Thanks to all contributors who have helped make LangBot better: