saiki
saikiはTypeScriptで構築された強力なツールで、開発者が効率的にコードを生成し、編集するための機能を提供します。直感的なインターフェースと豊富な機能により、開発プロセスを大幅に改善します。
GitHubスター
203
ユーザー評価
未評価
お気に入り
0
閲覧数
12
フォーク
33
イシュー
53
Dexto (formerly Saiki)
A lightweight runtime for creating and running AI agents that turn natural language into real-world actions.
Table of Contents
- Why Dexto?
- Installation
- Run Modes
- Quick Start
- Programmatic API
- Configuration
- Examples & Demos
- Capabilities
- LLM Providers
- Standalone MCP Manager
- CLI Reference
- Next Steps
- Community & Support
- Contributors
- License
Why Dexto?
Dexto is the missing intelligence layer of your stack—perfect for building AI applications, standalone chatbots, or as the reasoning engine inside larger products.
The main Dexto features are:
💡 Feature | What it means for you |
---|---|
Powerful CLI and Web UI | Dexto ships with a powerful CLI and Web UI that enable you to run AI agents in your terminal and over the web. |
Single runtime, many interfaces | Run the same agent via CLI, Web, Discord, Telegram, or a REST/WS server. |
Model-agnostic | Hot-swap LLMs from OpenAI, Anthropic, Gemini, Groq, or local models. |
Unified Tooling | Connect to remote tool servers (filesystem, browser, web-search) via the Model Context Protocol (MCP). |
Config-driven | Define agent behavior (prompts, tools, model, memory) in version-controlled YAML. |
Production-ready Core | Leverage a multi-session chat manager, typed API, pluggable storage, and robust logging. |
Extensible | Ship your own MCP tool servers or plug in custom services with a few lines of config. |
Multi-Agent Systems | Enable multi-agent collaboration via MCP and A2A. |
Installation
# NPM global
npm install -g dexto
# —or— build from source
git clone https://github.com/truffle-ai/dexto.git
cd dexto && npm i && npm run build && npm link
Run Modes
Mode | Command | Best for |
---|---|---|
Interactive CLI | dexto |
Everyday automation & quick tasks |
Web UI | dexto --mode web |
Friendly chat interface w/ image support |
Headless Server | dexto --mode server |
REST & WebSocket APIs for agent interaction |
MCP Server (Agent) | dexto --mode mcp |
Exposing your agent as a tool for others via stdio |
MCP Server (Aggregator) | dexto mcp --group-servers |
Re-exposing tools from multiple MCP servers via stdio |
Discord Bot | dexto --mode discord |
Community servers & channels (Requires Setup) |
Telegram Bot | dexto --mode telegram |
Mobile chat (Requires Setup) |
Run dexto --help
for all flags, sub-commands, and environment variables.
Quick Start
Set your API keys first:
export OPENAI_API_KEY=your_openai_api_key_here
Then, give Dexto a multi-step task that combines different tools:
dexto "create a new snake game in html, css, and javascript, then open it in the browser"
Dexto will use its filesystem tools to write the code and its browser tools to open the index.html
file—all from a single prompt.
Then start the Web UI:
dexto --mode web
The Web UI will load up any previous conversations you had, and also allows you to experiment with different models and MCP servers.
Programmatic API
The DextoAgent
class is the core of the runtime. The following example shows its full lifecycle: initialization, running a single task, holding a conversation, and shutting down.
import 'dotenv/config';
import { DextoAgent, loadConfigFile } from 'dexto';
const cfg = await loadConfigFile('./agents/default-agent.yml');
const agent = new DextoAgent(cfg);
await agent.start();
// Single-shot task
console.log(await agent.run('List the 5 largest files in this repo'));
// Conversation
await agent.run('Write a haiku about TypeScript');
await agent.run('Make it funnier');
agent.resetConversation();
await agent.stop();
Everything in the CLI is powered by this same class—so whatever the CLI can do, your code can too.
Check out our Typescript SDK docs for a complete guide.
Configuration
Agents are defined in version-controlled YAML. A minimal example:
mcpServers:
filesystem:
type: stdio
command: npx
args: ['-y', '@modelcontextprotocol/server-filesystem', '.']
puppeteer:
type: stdio
command: npx
args: ['-y', '@truffle-ai/puppeteer-server']
llm:
provider: openai
model: gpt-4o
apiKey: $OPENAI_API_KEY
systemPrompt: |
You are Dexto, an expert coding assistant...
Change the file, reload the agent, and chat—the conversation state, memory, and tools will update.
Check out our Configuration guide for the complete reference.
Examples & Demos
🛒 Amazon Shopping Assistant
Task: Can you go to amazon and add some snacks to my cart? I like trail mix, cheetos and maybe surprise me with something else?
# Default agent has browser tools
dexto
📧 Send Email Summaries to Slack
Task: Summarize emails and send highlights to Slack
dexto --agent ./agents/examples/email_slack.yml

More ready-to-run recipes live in agents/examples
and the docs site.
Capabilities
- Dynamic LLM Switching: Change model, provider, or routing rules mid-conversation.
- Streaming Responses: Opt-in to receive tokens as they arrive for real-time output.
- Multi-Session Management: Create isolated, stateful chat sessions (think workspace tabs).
- Pluggable Memory Backends: Use the in-memory default or connect your own DB via the
StorageManager
. - Lifecycle Event Bus: Subscribe to agent events for metrics, logging, or custom side-effects.
- Standalone MCP Manager: Use Dexto's core
MCPManager
in your own projects without the full agent.
LLM Providers
Dexto supports multiple LLM providers out-of-the-box, plus any OpenAI SDK-compatible provider.
- OpenAI:
gpt-4.1-mini
,gpt-4o
,o3
,o1
and more - Anthropic:
claude-4-sonnet-20250514
,claude-3-7-sonnet-20250219
, and more - Google:
gemini-2.5-pro
,gemini-2.0-flash
and more - Groq:
llama-3.3-70b-versatile
,gemma-2-9b-it
Quick Setup
Set your API key and run. You can switch providers instantly via the -m
flag.
# OpenAI (default)
export OPENAI_API_KEY=your_openai_api_key_here
export ANTHROPIC_API_KEY=your_anthropic_api_key_here
export GOOGLE_GENERATIVE_AI_API_KEY=your_google_gemini_api_key_here
dexto
# Switch providers via CLI
dexto -m claude-3.5-sonnet-20240620
dexto -m gemini-1.5-flash-latest
For comprehensive setup instructions, see our LLM Providers Guide.
Standalone MCP Manager
Need to manage MCP tool servers without the full agent? Use the MCPManager
directly in your own applications.
import { MCPManager } from 'dexto';
// Create manager instance
const manager = new MCPManager();
// Connect to MCP servers
await manager.connectServer('filesystem', {
type: 'stdio',
command: 'npx',
args: ['-y', '@modelcontextprotocol/server-filesystem', '.']
});
// Get all available tools across servers
const tools = await manager.getAllTools();
console.log('Available tools:', Object.keys(tools));
// Execute a tool
const result = await manager.executeTool('readFile', { path: './README.md' });
console.log('File contents:', result);
// Disconnect when done
await manager.disconnectAll();
See the MCP Manager Documentation for the complete API reference.
CLI Reference
Click to expand for full CLI reference (`dexto --help`)
Usage: dexto [options] [command] [prompt...]
The Dexto CLI allows you to talk to Dexto, build custom AI Agents, and create complex AI applications.
For full documentation, visit https://docs.dexto.ai.
Arguments:
prompt Natural-language prompt to run once. If empty, starts interactive CLI.
Options:
-v, --version output the current version
-a, --agent <path> Path to agent config file
-s, --strict Require all server connections to succeed
--no-verbose Disable verbose output
-m, --model <model> Specify the LLM model to use.
-r, --router <router> Specify the LLM router to use (vercel or in-built)
--mode <mode> Runtime mode: cli | web | server | discord | telegram | mcp (default: "cli")
--web-port <port> Optional port for the web UI (default: "3000")
-h, --help display help for command
Commands:
create-app Scaffold a new Dexto Typescript app.
init-app Initialize an existing Typescript app with Dexto.
mcp Run Dexto as an MCP server.
Next Steps
- Quick Start – Get up and running in minutes.
- Configuration Guide – Configure agents, LLMs, and tools.
- Building with Dexto – Developer guides and patterns.
- API Reference – REST APIs, WebSocket, and SDKs.
Contributing
We welcome contributions! Refer to our Contributing Guide for more details.
Community & Support
Dexto is built by the team at Truffle AI.
Join our Discord to share projects, ask questions, or just say hi!
If you enjoy Dexto, please give us a ⭐ on GitHub—it helps a lot!
Contributors
Thanks to all these amazing people for contributing to Dexto!
License
Elastic License 2.0. See LICENSE for full terms.