ChatGPT
AI conversational assistant for answering questions, writing, and coding help
Lobe Chat
Modern ChatGPT/LLM UI with multi-modal support and plugins
Open-source chat interface supporting OpenAI, Claude, Gemini, and local LLMs. Features speech synthesis, function calling plugins, and one-click deployment for private AI applications.
Overview
Modern AI Chat Interface for Developers and Power Users
LobeChat is a feature-rich chat UI and framework designed for users who want full control over their AI interactions. Built by design-engineers focused on modern UX, it provides a polished interface for ChatGPT, Claude, Gemini, Groq, Ollama, and other language models.
The platform supports multi-modal conversations (text, voice, images), speech synthesis (TTS) and recognition (STT), and an extensible plugin system via function calling. The Model Context Protocol (MCP) enables seamless integration with databases, APIs, file systems, and external services, transforming conversations into powerful workflows.
Deployment and Ecosystem
Deploy your private instance with one click to Vercel, Zeabur, Sealos, or via Docker. LobeChat supports both local and remote databases, multi-user management, and Progressive Web App (PWA) capabilities for mobile devices. The MCP Marketplace offers curated plugins to extend functionality, while the Agent Market provides pre-configured AI assistants. A dedicated desktop application delivers peak performance without browser limitations.
Whether you're a developer building custom AI tools or a user seeking a transparent, extensible chat experience, LobeChat provides the flexibility and modern design to match your workflow.
Highlights
MCP plugin system for connecting AI to databases, APIs, and external services
Multi-model support: OpenAI, Claude, Gemini, Groq, Ollama, and local LLMs
Speech synthesis (TTS), recognition (STT), and multi-modal conversations
One-click deployment to Vercel, Docker, or cloud platforms with multi-user management
Pros
- Extensive model provider support including local and cloud LLMs
- Rich plugin ecosystem via MCP and function calling for workflow automation
- Modern, customizable UI with PWA, desktop app, and mobile optimization
- Self-hostable with flexible deployment options and multi-user capabilities
Considerations
- Active development means features and APIs may change frequently
- Setup complexity increases with advanced features like MCP plugins and multi-user management
- Requires technical knowledge for self-hosting and custom plugin integration
- Documentation may lag behind rapid feature additions
Managed products teams compare with
When teams consider Lobe Chat, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Fit guide
Great for
- Developers building custom AI applications with extensible plugin architectures
- Teams needing private, self-hosted chat interfaces with multi-user support
- Power users wanting full control over model selection and conversation workflows
- Organizations integrating AI with existing databases, APIs, and internal tools
Not ideal when
- Non-technical users seeking zero-configuration, managed AI chat services
- Projects requiring enterprise SLAs and dedicated commercial support
- Users who prefer stable, feature-frozen software over rapid iteration
- Teams without infrastructure for self-hosting or cloud deployment
How teams use it
Private Enterprise AI Assistant
Deploy a self-hosted chat interface connected to internal databases and APIs, enabling employees to query company data securely without third-party services.
Multi-Model Research Platform
Compare responses from OpenAI, Claude, Gemini, and local models side-by-side to evaluate performance, cost, and accuracy for specific tasks.
Voice-Enabled Customer Support
Build a conversational AI with TTS/STT capabilities that integrates with CRM systems via MCP plugins, providing real-time customer assistance.
Developer Workflow Automation
Connect AI to GitHub, file systems, and development tools through function calling, automating code reviews, documentation generation, and issue triage.
Tech snapshot
TypeScript99%
HTML1%
JavaScript1%
Shell1%
MDX1%
Dockerfile1%
Frequently asked questions
What is the Model Context Protocol (MCP)?
MCP is a plugin system that enables LobeChat to connect with external tools, databases, APIs, and file systems. It allows your AI to interact dynamically with your digital ecosystem, transforming conversations into actionable workflows.
Can I use LobeChat without self-hosting?
Yes, you can visit the official website to use LobeChat immediately without installation or registration. For private deployments, one-click options are available for Vercel, Zeabur, and other platforms.
Which language models does LobeChat support?
LobeChat supports OpenAI (ChatGPT), Claude, Gemini, Groq, Ollama, and other local or cloud-based LLMs. You can switch between providers and models within the same interface.
Does LobeChat support voice conversations?
Yes, LobeChat includes text-to-speech (TTS) and speech-to-text (STT) capabilities, enabling full voice-based interactions with your AI assistant.
Is LobeChat suitable for team or multi-user deployments?
Yes, LobeChat supports multi-user management and can be deployed with local or remote databases, making it suitable for team and organizational use cases.
Project at a glance
Active- Stars
- 70,367
- Watchers
- 70,367
- Forks
- 14,438
Repo age2 years old
Last commit9 hours ago
Self-hostingSupported
Primary languageTypeScript
Last synced 8 hours ago