What it does

DeepChat is an Electron-based desktop chat client that connects to pretty much every LLM provider—OpenAI, Anthropic, Gemini, DeepSeek, Grok, Moonshot, and local Ollama instances—without making you juggle separate apps. It wraps conversations in a multi-window, multi-tab shell that the authors compare to using a browser, so you can run parallel sessions without blocking.

Beyond basic chat, it layers on three extension mechanisms: MCP (Model Context Protocol) for tool calling and resources, installable “Skills” that load task-specific instructions and scripts per conversation, and ACP (Agent Client Protocol) integration that lets you run external agents as selectable “models” with their own workspace UI. There’s also remote control via Telegram, Discord, Feishu/Lark, QQBot, and WeChat iLink.

The interesting bit

The ACP integration is the unusual angle. Instead of treating agents as black-box APIs, DeepChat runs ACP-compatible agents as first-class models inside a dedicated workspace with structured plans, tool calls, and terminal output. It’s an attempt to make external agent runtimes feel native rather than bolted-on. The built-in MCP support is also notably complete—Resources, Prompts, Tools, plus inMemory services for code execution and file operations that work without secondary installation.

Key highlights

• Multi-tab, multi-window architecture for parallel non-blocking sessions
• Built-in Ollama management (download, deploy, run) without touching the command line
• Full MCP protocol support with StreamableHTTP/SSE/Stdio transports and built-in Node.js runtime
• Skills system compatible with Claude Code, Cursor, Copilot, and other agent tools; import/export via folders, ZIPs, or URLs
• ACP agent integration with native workspace UI
• Remote session control from major messaging platforms
• Apache 2.0 licensed, with claimed “reserved encryption interfaces” for enterprise hardening

Caveats

• The README’s security claims (“reserved encryption interfaces and code obfuscation capabilities”) are vague—actual implementation details aren’t shown
• “Excellent performance” and “rejecting simple web wrappers” are assertions without benchmarks in the sources
• The project is young enough that the 5,867 stars may reflect feature ambition as much as proven stability

Verdict

Worth a look if you want one desktop app to rule multiple LLMs and you’re intrigued by agent protocols beyond basic chat. Skip it if you’re happy with your current client or need battle-tested enterprise security with documented compliance.