@DanKornas: Running serious AI work across separate model apps, tool interfaces, and messaging clients creates avoidable friction. …

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open-source local-first ai-agent desktop-client mcp-support multi-model

Summary

DeepChat is an open-source, local-first AI agent desktop client that unifies models, tools, and agent runtimes with session history, MCP support, and remote control via messaging platforms.

Running serious AI work across separate model apps, tool interfaces, and messaging clients creates avoidable friction. DeepChat is an open-source, local-first AI agent desktop client for builders who want models, tools, and agent runtimes in one app. It helps you manage long-running agent work by preserving structured session history and bringing MCP, Skills, ACP agents, and remote controls into one desktop interface. Key features: • Multi-model support – connect cloud providers or locally deployed Ollama models. • Tape & Trace – retain recoverable session history and inspect requests, metadata, included entries, and token budgets. • MCP support – use Resources, Prompts, and Tools through StreamableHTTP, SSE, or Stdio transports. • Skills and ACP – install task-specific Skills and run ACP-compatible agents from the model selector. • Remote control – manage bound sessions from Telegram, Feishu/Lark, QQBot, Discord, or WeChat iLink. It’s open-source (Apache License 2.0). Link in the reply
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Cached at: 07/22/26, 04:21 AM

Running serious AI work across separate model apps, tool interfaces, and messaging clients creates avoidable friction.

DeepChat is an open-source, local-first AI agent desktop client for builders who want models, tools, and agent runtimes in one app.

It helps you manage long-running agent work by preserving structured session history and bringing MCP, Skills, ACP agents, and remote controls into one desktop interface.

Key features: • Multi-model support – connect cloud providers or locally deployed Ollama models. • Tape & Trace – retain recoverable session history and inspect requests, metadata, included entries, and token budgets. • MCP support – use Resources, Prompts, and Tools through StreamableHTTP, SSE, or Stdio transports. • Skills and ACP – install task-specific Skills and run ACP-compatible agents from the model selector. • Remote control – manage bound sessions from Telegram, Feishu/Lark, QQBot, Discord, or WeChat iLink.

It’s open-source (Apache License 2.0).

Link in the reply

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