T
truffle-ai/dexto
Harness, CLI and SDKs for building agents
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
客户端配置（取自该仓库的安装命令）
{
"mcpServers": {
"truffle-ai-dexto": {
"command": "npx",
"args": ["args"]
}
}
}解析自我们于 2026-11-06 抓取的该仓库 README；我们未执行过。
command/args 来自仓库写明的安装命令；不确定时请以该项目 README 为准。
VS Code（.vscode/mcp.json —— 键名是 servers）
{
"servers": {
"truffle-ai-dexto": {
"command": "npx",
"args": ["args"]
}
}
}VS Code 顶层键是 <code>servers</code>，其余与上面那份相同。
Claude Code（命令行）
claude mcp add --transport stdio truffle-ai-dexto -- npx args
Claude Code 不收 JSON 文件，用这条命令直接加。
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
npx args
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
npx args。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。
Deutsch |
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
English |
Español |
français |
日本語 |
한국어 |
Português |
Русский |
中文
An open agent harness for AI applications—ships with a powerful coding agent.
## What is Dexto?
Dexto is an agent harness—the orchestration layer that turns LLMs into reliable, stateful agents that can take actions, remember context, and recover from errors.
Think of it like an operating system for AI agents:
| Component | Analogy | Role |
| LLM | CPU | Raw processing power |
| Context Window | RAM | Working memory |
| Dexto | Operating System | Orchestration, state, tools, recovery |
| Your Agent | Application | Domain-specific logic and clients |
### Why Dexto?
Configuration-driven: Define agents in YAML. Swap models and tools without touching code.
Batteries included: Session management, tool orchestration, memory, multimodal support, and observability—out of the box.
Run anywhere: Local, cloud, or hybrid. CLI, Web UI, REST API, Discord, Telegram, or embedded in your app.
### What You Can Build
Coding Agents – Build, debug, and refactor code autonomously
Autonomous Agents – Plan, execute, and adapt to user goals
Digital Companions – Assistants that remember context and anticipate needs
MCP Clients & Servers – Connect tools, files, APIs via Model Context Protocol
Multi-Agent Systems – Agents that collaborate, delegate, and solve complex tasks together
## Coding Agent
Dexto ships with a production-ready coding agent you can use immediately via the CLI or Web UI.
bash
# Launch the coding agent (default)
dexto
# Or explicitly
dexto --agent coding-agent
What it can do:
Build new apps from scratch
Read, write, and refactor code across your entire codebase
Execute shell commands and run tests
Spawn specialized sub-agents for exploration and planning
Remember context across sessions with persistent memory
Work with any of 50+ LLMs (swap models mid-conversation)
Ready-to-use interfaces:
Web UI – Chat interface with file uploads, syntax highlighting, and MCP tool browser
CLI – Terminal-native with /commands, streaming output, and session management
The coding agent is just one example of what you can build. Create your own agents by defining a YAML config—same architecture, your domain.
## Quick Start
### Install
bash
# macOS / Linux / WSL (native installer, recommended)
curl -fsSL https://dexto.ai/install | bash
# Windows PowerShell
irm https://dexto.ai/install.ps1 | iex
# Or build from source
git clone https://github.com/truffle-ai/dexto.git
cd dexto && pnpm install && pnpm install-cli
Upgrade/uninstall and migration troubleshooting live in docs:
Installation guide: https://cli.dexto.ai/docs/getting-started/installation
CLI command reference: https://cli.dexto.ai/docs/guides/cli/overview
### Run
bash
# Start Dexto (launches setup wizard on first run)
dexto
More options:
bash
dexto --mode cli # Terminal mode
dexto -p "create a landing page for a coffee shop" # One-shot task
dexto --auto-approve "refactor this codebase" # Skip confirmations
dexto -m claude-sonnet-4-5-20250929 # Switch models
dexto --help # Explore all options
Inside the interactive CLI, type / to explore commands—switch models, manage sessions, configure tools, and more.
### Manage Settings
bash
# Configure defaults like LLM provider/model, API keys, or download local models
Español |
français |
日本語 |
한국어 |
Português |
Русский |
中文
An open agent harness for AI applications—ships with a powerful coding agent.
## What is Dexto?
Dexto is an agent harness—the orchestration layer that turns LLMs into reliable, stateful agents that can take actions, remember context, and recover from errors.
Think of it like an operating system for AI agents:
| Component | Analogy | Role |
| LLM | CPU | Raw processing power |
| Context Window | RAM | Working memory |
| Dexto | Operating System | Orchestration, state, tools, recovery |
| Your Agent | Application | Domain-specific logic and clients |
### Why Dexto?
Configuration-driven: Define agents in YAML. Swap models and tools without touching code.
Batteries included: Session management, tool orchestration, memory, multimodal support, and observability—out of the box.
Run anywhere: Local, cloud, or hybrid. CLI, Web UI, REST API, Discord, Telegram, or embedded in your app.
### What You Can Build
Coding Agents – Build, debug, and refactor code autonomously
Autonomous Agents – Plan, execute, and adapt to user goals
Digital Companions – Assistants that remember context and anticipate needs
MCP Clients & Servers – Connect tools, files, APIs via Model Context Protocol
Multi-Agent Systems – Agents that collaborate, delegate, and solve complex tasks together
## Coding Agent
Dexto ships with a production-ready coding agent you can use immediately via the CLI or Web UI.
bash
# Launch the coding agent (default)
dexto
# Or explicitly
dexto --agent coding-agent
What it can do:
Build new apps from scratch
Read, write, and refactor code across your entire codebase
Execute shell commands and run tests
Spawn specialized sub-agents for exploration and planning
Remember context across sessions with persistent memory
Work with any of 50+ LLMs (swap models mid-conversation)
Ready-to-use interfaces:
Web UI – Chat interface with file uploads, syntax highlighting, and MCP tool browser
CLI – Terminal-native with /commands, streaming output, and session management
The coding agent is just one example of what you can build. Create your own agents by defining a YAML config—same architecture, your domain.
## Quick Start
### Install
bash
# macOS / Linux / WSL (native installer, recommended)
curl -fsSL https://dexto.ai/install | bash
# Windows PowerShell
irm https://dexto.ai/install.ps1 | iex
# Or build from source
git clone https://github.com/truffle-ai/dexto.git
cd dexto && pnpm install && pnpm install-cli
Upgrade/uninstall and migration troubleshooting live in docs:
Installation guide: https://cli.dexto.ai/docs/getting-started/installation
CLI command reference: https://cli.dexto.ai/docs/guides/cli/overview
### Run
bash
# Start Dexto (launches setup wizard on first run)
dexto
More options:
bash
dexto --mode cli # Terminal mode
dexto -p "create a landing page for a coffee shop" # One-shot task
dexto --auto-approve "refactor this codebase" # Skip confirmations
dexto -m claude-sonnet-4-5-20250929 # Switch models
dexto --help # Explore all options
Inside the interactive CLI, type / to explore commands—switch models, manage sessions, configure tools, and more.
### Manage Settings
bash
# Configure defaults like LLM provider/model, API keys, or download local models
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/truffle-ai-dexto/)
- 来源
- awesome · https://github.com/truffle-ai/dexto
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