T
ThinkInAIXYZ/deepchat
Desktop assistant that connects models to personal tools
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
取自该仓库的安装命令
pip install setuptools
解析自我们于 2026-11-06 抓取的该仓库 README;我们未执行过。
这条是仓库自己写的安装方式,不是 MCP 客户端配置,所以不生成 JSON。
配置项的键名以你的客户端为准:客户端与 CLI
- 来源明细
- 收录自 abordage/awesome-mcp 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
- 收录与活跃
- 收录于 2026-11-05 · 最近见到 2026-11-14 · 共见到 10 次 · 被 10 个来源列出
- 评分构成
- 综合分 1,003 · 10 个来源 · mcp
- 安装
pip install setuptools
常见问题(答案都来自我们的记录)
怎么安装?
该仓库给出的安装命令是
pip install setuptools。我们的记录里它是仓库自己提供的;不保证在你的客户端上直接可用。它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
我们收录于 2026-11-05;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
DeepChat - Open-Source Local-First AI Agent Desktop Client
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
DeepChat is an open-source, local-first AI agent desktop client with rich agent capabilities, designed around the Tape.systems philosophy, with support for MCP, Skills, ACP, and remote control integrations for messaging apps.
中文 / English / 日本語
## 📑 Table of Contents
📑 Table of Contents
🚀 Project Introduction
💡 Why Choose DeepChat
📦 Quick Start
Download and Install
Configure Models
Start Conversations
🔥 Main Features
📼 Tape & Trace
🧠 Skills Support
🧩 ACP Integration (Agent Client Protocol)
📡 Remote Control
🤖 Supported Model Providers
Compatible with any model provider in OpenAI/Gemini/Anthropic API format
🔍 Use Cases
💻 Development Guide
Install Dependencies
Start Development
Build
👥 Community \& Contribution
⭐ Star History
👨💻 Contributors
📃 License
## 🚀 Project Introduction
DeepChat is a powerful open-source, local-first AI agent desktop client that brings together models, tools, Skills, agent runtimes, Tape, and long-running sessions in one desktop app. Whether you're using cloud APIs like OpenAI, Gemini, Anthropic, or locally deployed Ollama models, DeepChat delivers a smooth user experience.
DeepChat's sessions and agent processes follow the Tape.systems philosophy: keep the process, so context, tool calls, requests, and results stay recoverable, traceable, and inspectable. It also provides strong MCP support, installable Skills, ACP agent integration, and remote control for Telegram, Feishu/Lark, QQBot, Discord, WeChat iLink, and other messaging workflows.
## 💡 Why Choose DeepChat
Compared to other AI tools, DeepChat offers the following unique advantages:
Local-First Agent Desktop Client: Run DeepChat agents, ACP agents, and remote-ready bots in one local app
Tape.systems Philosophy: Preserve recoverable session history, trace request context, and inspect token budgets when agent work gets complex
Skills That Travel: Install, import, export, and enable reusable Skills per conversation for code review, documents, frontend work, Office/PDF tasks, and more
Native ACP Integration: Run ACP-compatible coding and task agents as first-class entries in the model selector
Strong MCP Support: Support Resources, Prompts, Tools, multiple transports, inMemory services, and one-click installation
Remote-Ready Workflows: Control DeepChat sessions from Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink
Unified Multi-Model Management: One application supports mainstream cloud LLMs and local Ollama models, eliminating the need to switch between multiple apps
Privacy-Focused: Local data storage and network proxy support reduce the risk of information leakage
Business-Friendly: Embraces open source under the Apache License 2.0, suitable for both commercial and personal use
## 📦 Quick Start
### Download and Install
You can install DeepChat using one of the following methods:
Option 1: GitHub Releases
Download the latest version for your system from the GitHub Releases page:
Windows: .exe installation file
macOS: .dmg installation file
Linux: .AppImage or .deb installation file
Option 2: Official Website
Download from the official website.
Option 3: Homebrew (macOS only)
For macOS users, you can install DeepChat using Homebrew:
中文 / English / 日本語
## 📑 Table of Contents
📑 Table of Contents
🚀 Project Introduction
💡 Why Choose DeepChat
📦 Quick Start
Download and Install
Configure Models
Start Conversations
🔥 Main Features
📼 Tape & Trace
🧠 Skills Support
🧩 ACP Integration (Agent Client Protocol)
📡 Remote Control
🤖 Supported Model Providers
Compatible with any model provider in OpenAI/Gemini/Anthropic API format
🔍 Use Cases
💻 Development Guide
Install Dependencies
Start Development
Build
👥 Community \& Contribution
⭐ Star History
👨💻 Contributors
📃 License
## 🚀 Project Introduction
DeepChat is a powerful open-source, local-first AI agent desktop client that brings together models, tools, Skills, agent runtimes, Tape, and long-running sessions in one desktop app. Whether you're using cloud APIs like OpenAI, Gemini, Anthropic, or locally deployed Ollama models, DeepChat delivers a smooth user experience.
DeepChat's sessions and agent processes follow the Tape.systems philosophy: keep the process, so context, tool calls, requests, and results stay recoverable, traceable, and inspectable. It also provides strong MCP support, installable Skills, ACP agent integration, and remote control for Telegram, Feishu/Lark, QQBot, Discord, WeChat iLink, and other messaging workflows.
## 💡 Why Choose DeepChat
Compared to other AI tools, DeepChat offers the following unique advantages:
Local-First Agent Desktop Client: Run DeepChat agents, ACP agents, and remote-ready bots in one local app
Tape.systems Philosophy: Preserve recoverable session history, trace request context, and inspect token budgets when agent work gets complex
Skills That Travel: Install, import, export, and enable reusable Skills per conversation for code review, documents, frontend work, Office/PDF tasks, and more
Native ACP Integration: Run ACP-compatible coding and task agents as first-class entries in the model selector
Strong MCP Support: Support Resources, Prompts, Tools, multiple transports, inMemory services, and one-click installation
Remote-Ready Workflows: Control DeepChat sessions from Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink
Unified Multi-Model Management: One application supports mainstream cloud LLMs and local Ollama models, eliminating the need to switch between multiple apps
Privacy-Focused: Local data storage and network proxy support reduce the risk of information leakage
Business-Friendly: Embraces open source under the Apache License 2.0, suitable for both commercial and personal use
## 📦 Quick Start
### Download and Install
You can install DeepChat using one of the following methods:
Option 1: GitHub Releases
Download the latest version for your system from the GitHub Releases page:
Windows: .exe installation file
macOS: .dmg installation file
Linux: .AppImage or .deb installation file
Option 2: Official Website
Download from the official website.
Option 3: Homebrew (macOS only)
For macOS users, you can install DeepChat using Homebrew:
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
[](https://anclum.com/zh/s/thinkinaixyz-deepchat/)
- 来源
- awesome · https://github.com/ThinkInAIXYZ/deepchat
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