T
truffle-ai/dexto
Harness, CLI and SDKs for building agents
View on GitHub ↗Link checked 2026-11-12 · HTTP 200 · opens the vendor's own site
Install & config
Client config (built from the install command this repo gives)
{
"mcpServers": {
"truffle-ai-dexto": {
"command": "npx",
"args": ["args"]
}
}
}Parsed from the README we fetched on 2026-11-06; we have not executed it.
command/args come from the install command the repository states. When it is ambiguous, the project README wins.
VS Code (.vscode/mcp.json - the key is servers)
{
"servers": {
"truffle-ai-dexto": {
"command": "npx",
"args": ["args"]
}
}
}Same server, but VS Code keeps it under <code>servers</code>.
Claude Code (command line)
claude mcp add --transport stdio truffle-ai-dexto -- npx args
Claude Code does not read a config file; add the server with this command.
Key names differ by client: Clients & CLI
- Source
- collected from the abordage/awesome-mcp list · type: MCP server
- Harvest history
- first seen 2026-11-05 · last seen 2026-11-14 · seen 10× · listed by 10 sources
- Score
- score 1,003 · 10 sources · mcp
- Install
npx args
FAQ (answers come from our records)
How do I install it?
The repository provides this install command:
npx args. It comes from the repository itself; we cannot guarantee it runs as-is in your client.Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
first catalogued 2026-11-05；last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.
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
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