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Production-grade platform for building agentic IM bots

Project description

LangBot

LangBot - Production-grade IM bot made easy. | Product Hunt

Production-grade platform for building agentic IM bots.

Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.

English / 简体中文 / 繁體中文 / 日本語 / Español / Français / 한국어 / Русский / Tiếng Việt

Discord Ask DeepWiki GitHub release (latest by date) python GitHub stars

WebsiteFeaturesDocsAPICloudPlugin MarketRoadmap


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.

LangBot web management dashboard — real-time monitoring of message volume, model calls, success rate and active sessions

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.

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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

Deploy on Zeabur Deploy on Railway

More options: Docker · Manual · BTPanel · Kubernetes


Supported Platforms

Platform Status Notes
Discord Official
Telegram Official
Slack Official
LINE Official
QQ Personal & Official API (Channel, DM, Group)
WeCom Enterprise WeChat, External CS, AI Bot
WeChat Personal & Official Account
Lark Official
DingTalk Official
KOOK Official
Satori
Email Matrix, Satori
Matrix Supports multiple bridged platforms such as Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip, and more

Supported LLMs & Integrations

Provider Type Status
OpenAI LLM
Anthropic LLM
DeepSeek LLM
Google Gemini LLM
xAI LLM
Moonshot LLM
Zhipu AI LLM
Ollama Local LLM
LM Studio Local LLM
Dify LLMOps
MCP Protocol
SiliconFlow Gateway
Aliyun Bailian Gateway
Volc Engine Ark Gateway
ModelScope Gateway
GiteeAI Gateway
CompShare GPU Platform
PPIO GPU Platform
ShengSuanYun GPU Platform
接口 AI Gateway
302.AI Gateway
Qiniu Gateway

→ View all integrations


Why LangBot?

Use Case How LangBot Helps
Customer Support Deploy AI agents to Slack/Discord/Telegram that answer questions using your knowledge base
Internal Tools Connect n8n/Dify workflows to WeCom/DingTalk for automated business processes
Community Management Moderate QQ/Discord groups with AI-powered content filtering and interaction
Multi-Platform Presence One bot, all platforms. Manage from a single dashboard

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.


Live Demo

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

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

Note: Public demo environment. Do not enter sensitive information.


Community

Discord


Star History

Star History Chart


Contributors

Thanks to all contributors who have helped make LangBot better:

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