← Back to directory
N

NextChat

Community
Light and Fast AI Assistant
GitHub source repository ↗
★ 88.6k Stars Category · Other Very popular Source revision defdcdb55d85
29FMRS · D
Reliability
2/20
Security and permissions
5/20
Maintenance
16/20
Documentation
3/20
Setup experience
3/20

NextChat is a flexible open-source AI chat client that supports multiple models and cross-platform deployment. However, it is not an official MCP server, and users must pay attention to security configuration.

Read the FMRS scoring method →

NextChat is a cross-platform AI chat client that runs on Web, iOS, macOS, Android, Linux, and Windows. It supports multiple AI model providers, including OpenAI GPT-4, Anthropic Claude, Google Gemini Pro, DeepSeek, and more. NextChat prioritizes privacy by storing all data locally in the browser. MCP functionality can be enabled via the environment variable ENABLE_MCP=true.

Tools

The tool list has not been reviewed yet.

Setup

  1. Get an OpenAI API key (optional).
  2. Deploy with one click on Vercel or run locally (requires Node.js >= 18).
  3. To enable MCP, set the environment variable ENABLE_MCP=true and then start the application.

Fit and risk

Best for

  • Users who want a self-hosted or open-source chat client
  • Users who need cross-platform access to AI models
  • Developers or enterprises wanting a customizable AI chat UI

Not for

  • Production-grade AI services requiring official support
  • Non-technical users looking for a ready-to-use AI service (may require configuration)
  • Enterprises with strict data governance requirements (data is stored locally in the browser by default)

Required permissions

  • Network access to call AI model APIs
  • Local storage in the browser (e.g., chat history, settings)
  • When using MCP, may connect to local or remote tools

Risks and side effects

  • This server is not an official product but a community-maintained open-source project, which may be less stable than official versions.
  • If self-hosted, API key security is crucial and must be protected.
  • Relying on third-party deployment services (e.g., Vercel) may introduce data security risks.
  • Enabling MCP features increases the attack surface.

Troubleshooting

  1. If API calls fail, check BASE_URL and API key configuration.
  2. If the page is inaccessible, check the environment variable CODE (acts as an access password).
  3. If MCP is not effective, confirm ENABLE_MCP=true is set and restart the application.

Use cases

Chatting via a web or desktop interface
Managing multiple AI providers (e.g., OpenAI, Claude, Gemini)
Deploying a private AI assistant locally

Supported clients

Supported clients have not been confirmed yet.