MCPとツール呼び出し

DeepChat - Open-Source Local-First AI Agent Desktop Client

thinkinaixyz/deepchat

DeepChat is an open-source, local-first AI agent desktop client built in TypeScript and Electron. It integrates cloud LLMs, local models, MCP services, installable Skills, ACP agents, and remote control for messaging apps, following the Tape.systems philosophy to keep agent sessions recoverable and inspectable.

★ 6.2Kスター
⑂ 712フォーク数
6未解決の問題
TypeScript言語
Apache-2.0ライセンス
Q@project.QualityScore編集部スコア

プロジェクトのスクリーンショット

DeepChat - Open-Source Local-First AI Agent Desktop Clientのスクリーンショット DeepChat - Open-Source Local-First AI Agent Desktop Clientのスクリーンショット

概要

DeepChat unifies multi-model management, agent runtimes, and long-running sessions into a single desktop application. It supports a wide range of cloud LLM providers and local Ollama models. The application is designed around the Tape.systems philosophy, preserving structured session history, request context, tool calls, and token budgets for debugging and recovery. It features robust MCP support, ACP integration for external coding/task agents, and remote control capabilities via Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink.

主な機能

  • Local-first AI agent desktop client
  • Tape.systems philosophy for recoverable and traceable sessions
  • Installable and portable Skills compatible with Claude Code, Codex, Cursor, and more
  • Native ACP (Agent Client Protocol) integration
  • Strong MCP support with Resources, Prompts, Tools, and multiple transports
  • Remote control via Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink
  • Unified multi-model management for cloud and local models
  • Multi-window and multi-tab parallel session architecture
  • Artifacts rendering, Mermaid diagrams, and multi-modal content support
  • Built-in search integration with BoSearch, Brave Search, and simulated web browsing for Google, Bing, Baidu
  • DeepLink support for one-click MCP installation and conversation initiation
  • Cross-platform support for Windows, macOS, and Linux

要件、インストール、クイックスタート

End-users can install via GitHub Releases (.exe for Windows, .dmg for macOS, .AppImage/.deb for Linux), the official website, or Homebrew for macOS (brew install --cask deepchat). For development: run 'pnpm install' followed by 'pnpm run installRuntime'. If 'No module named distutils' error occurs, run 'pip install setuptools'.

使用方法

After installation, launch the app, open settings, and configure Model Providers with API keys or local Ollama. Create a new conversation with the '+' button, select a model, and begin chatting. Skills can be managed via Settings -> Skills, ACP agents via Settings -> ACP Agents, and remote channels via Settings -> Remote.

モデルの互換性とユースケース

Compatible with any model provider using OpenAI, Gemini, or Anthropic API formats. Explicitly supported providers include DeepSeek, OpenAI, Moonshot/Kimi, Grok, Gemini, Anthropic, Ollama, Qiniu, New API, Zhipu, PPIO, MiniMax, Fireworks, AIHubMix, Doubao, DashScope, Groq, JieKou.AI, ZenMux, GitHub Models, LM Studio, Hunyuan, 302.AI, Together, Poe, Vercel AI Gateway, OpenRouter, Azure OpenAI, TokenFlux, BurnCloud, OpenAI Responses, CherryIn, ModelScope, AWS Bedrock, Voice.ai, Vertex AI, GitHub Copilot, Xiaomi, o3.fan, Novita AI, Astraflow, SiliconFlow, and OrcaRouter.

ライセンスとリスクに関する注意事項

Licensed under the Apache License 2.0. Suitable for both commercial and personal use. Enterprise integration is supported with minimal configuration code changes to utilize reserved encrypted obfuscation security capabilities.

Editorial verification 2026-08-09: repository URL, owner, description, license and repository statistics were reviewed. License metadata: Apache-2.0. README was fetched for the channel draft; re-check repository dependencies, releases and model terms before production use.

リリースとメンテナンス

The repository was created on 2025-02-14. It currently has 6205 stars, 712 forks, and 6 open issues. The default branch is 'dev'. The last push was recorded on 2026-08-09.

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