📑 Table of Contents
🚀 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
🔥 Main Features
- 🤖 Local-First Agent Desktop Client
- Select DeepChat, ACP, and remote-capable agents from one model-like entry point
- Run long-lived sessions with project folders, permission modes, tool output, and resumable context
- 📼 Tape & Trace
- Session Tape records structured work history for recovery, resume, and future agent memory flows
- Trace previews show request sequences, provider/model metadata, Tape view manifests, included entries, and token budgets
- 🧠 Skills
- Install Skills from folders, ZIP files, or URLs
- Enable Skills per conversation so DeepChat can load task-specific instructions, references, and optional scripts
- Import and export Skills with Claude Code, Codex, Cursor, Windsurf, GitHub Copilot, and other compatible tools
- 🤝 ACP (Agent Client Protocol) Agent Integration
- Run ACP-compatible agents (built-in or custom commands) as selectable “models”
- ACP workspace UI for structured plans, tool calls, and terminal output when provided by the agent
- 📡 Remote Control
- Control DeepChat sessions from Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink
- Bind remote endpoints to sessions, switch models, answer pending interactions, stop runs, and open desktop sessions remotely
- 🌐 Multiple Cloud LLM Provider Support: DeepSeek, OpenAI, Moonshot/Kimi, Grok, Gemini, Anthropic, and more
- 🏠 Local Model Deployment Support:
- Integrated Ollama with comprehensive management capabilities
- Control and manage Ollama model downloads, deployments, and runs without command-line operations
- 🚀 Rich and Easy-to-Use Chat Capabilities
- Complete Markdown rendering with code block rendering based on industry-leading CodeMirror
- Multi-window + multi-tab architecture supporting parallel multi-session operations across all dimensions, use large models like using a browser, non-blocking experience brings excellent efficiency
- Supports Artifacts rendering for diverse result presentation
- Messages support retry to generate multiple variations; conversations can be forked freely, ensuring there's always a suitable line of thought
- Supports rendering images, Mermaid diagrams, and other multi-modal content; supports GPT-4o, Gemini, Grok text-to-image capabilities
- Supports highlighting external information sources like search results within the content
For more details on how to use these features, see the documentation index.
📼 Tape & Trace
DeepChat's session Tape follows the Tape.systems philosophy and keeps agent work recoverable and inspectable. Trace previews expose request sequences, provider/model metadata, Tape view manifests, included or excluded entries, and token budgets, making long-running agent sessions easier to debug and resume.
🧠 Skills Support
DeepChat Skills are designed to be compatible with the standard Agent Skills specification. A Skill can include task instructions, reference files, assets, and optional scripts, so DeepChat can act more like a domain specialist after it is enabled.
You can install Skills from folders, ZIP files, or URLs, and import/export them with Claude Code, Codex, Cursor, Windsurf, GitHub Copilot, Kiro, Antigravity, OpenCode, Goose, Kilo Code, and other compatible tools.
Built-in Skills cover generative art, code review, DeepChat settings, document collaboration, DOCX, frontend design, git commit messages, infographic syntax, MCP building, PDF, PPTX, Skill creation, Web Artifacts, and XLSX workflows.
Quick start:
- Open Settings → Skills
- Install or import a Skill
- Enable it in conversations that need that capability
🧩 ACP Integration (Agent Client Protocol)
DeepChat has built-in support for Agent Client Protocol (ACP), allowing you to integrate external agent runtimes into DeepChat with a native UI. Once enabled, ACP agents appear as first-class entries in the model selector, so you can use coding agents and task agents directly inside DeepChat.
Quick start: