OpenClaw

OpenClaw is an open-source AI agent workspace with multi-provider support, providing developers with a complete solution for building, deploying, and managing AI agents. With OpenClaw, developers can easily create cross-platform intelligent assistants and implement complex automation tasks.

Core Features

Multi-Provider Support

• Major AI Integrations: Supports OpenAI, Anthropic, Google Gemini, DeepSeek, and other large language models
• Flexible Switching: Seamlessly switch between providers within the same project without modifying core code
• Unified Interface: Provides a unified API interface, simplifying multi-provider integration complexity

Powerful Agent Framework

• Composable Architecture: Build reusable agent capabilities through Skills and MCP (Model Context Protocol)
• Workflow Orchestration: Supports complex multi-step workflows and task orchestration
• Memory Management: Built-in long-term and short-term memory management mechanisms

Developer Toolchain

• CLI Tool: Powerful command-line tool supporting project creation, building, testing, and deployment
• Debugging: Provides detailed execution logs and debugging information
• Hot Reload: Supports code hot reloading during development for improved efficiency

Technical Architecture

Layered Design

┌─────────────────────────────────────┐
│         Agent Layer                 │
│   (Skills, MCPs, Memory)            │
├─────────────────────────────────────┤
│         Core Layer                  │
│   (Orchestration, Planning)         │
├─────────────────────────────────────┤
│        Provider Layer               │
│   (OpenAI, Anthropic, etc.)         │
├─────────────────────────────────────┤
│         Infrastructure               │
│   (Storage, Network, Auth)          │
└─────────────────────────────────────┘

Core Components

1. Workspace

   • Project management and workspace isolation
   • Configuration management and environment variables
   • Plugin system extensibility

2. Agent Engine

   • Task decomposition and planning
   • Execution engine and state management
   • Error handling and retry mechanisms

3. Skills System

   • Reusable skill modules
   • Standardized interface definitions
   • Community sharing mechanisms

4. MCP (Model Context Protocol)

   • Standardized context protocol
   • Tool integration interface
   • Resource access control

Use Cases

1. Enterprise Automation

• Customer service chatbots
• Document processing and analysis
• Process automation

2. Development Assistance

• Code generation and review
• Test case generation
• API documentation authoring

3. Data Analysis

• Data cleaning and transformation
• Report generation
• Visualization recommendations

4. Content Creation

• Article writing and editing
• Multi-language translation
• Marketing copy generation

Getting Started

Installation

# Install via npm
npm install -g @openclaw/cli

# Or via Homebrew (macOS)
brew install openclaw

# Verify installation
claw --version

Create a Project

# Create a new project
claw create my-agent

# Enter the project directory
cd my-agent

# Install dependencies
npm install

# Start the development server
claw dev

Configure Providers

// claw.config.ts
export default {
  providers: [
    {
      name: 'openai',
      apiKey: process.env.OPENAI_API_KEY,
      model: 'gpt-4o'
    },
    {
      name: 'anthropic',
      apiKey: process.env.ANTHROPIC_API_KEY,
      model: 'claude-sonnet-4-20250514'
    }
  ],
  defaultProvider: 'openai',
  skills: [
    './skills/coding',
    './skills/web-search'
  ]
};

Create Your First Agent

// src/agent.ts
import { Agent, agent } from '@openclaw/core';

@agent('my-agent')
export class MyAgent extends Agent {
  async handleTask(task: string): Promise<string> {
    // Implement your agent logic
    return `Processed: ${task}`;
  }
}

Skills Development

OpenClaw’s Skills system lets you create reusable capability modules:

// skills/web-search/src/index.ts
import { Skill, skill } from '@openclaw/core';

@skill({
  name: 'web-search',
  description: 'Search the web for information',
  parameters: {
    query: { type: 'string', description: 'Search query' }
  }
})
export class WebSearchSkill extends Skill {
  async execute(query: string): Promise<string> {
    // Implement search logic
    return `Search results for: ${query}`;
  }
}

MCP Integration

MCP (Model Context Protocol) provides a standardized way to integrate tools:

// mcps/github/src/index.ts
import { MCP, mcp } from '@openclaw/core';

@mcp({
  name: 'github',
  description: 'GitHub integration for repository operations',
  tools: ['createIssue', 'listPRs', 'getFile']
})
export class GitHubMCP extends MCP {
  // Implement GitHub operations
}

Deployment & Operations

Local Deployment

# Build the project
claw build

# Run the production build
claw start

Cloud Deployment

# Deploy to Cloudflare Workers
claw deploy --platform workers

# Deploy to Vercel
claw deploy --platform vercel

Monitoring & Logging

# View runtime logs
claw logs

# Monitor performance metrics
claw monitor

Community & Ecosystem

Official Resources

• Documentation: https://docs.openclaw.ai
• GitHub: https://github.com/openclaw/openclaw
• Discord Community: https://discord.gg/clawd

Contributing

• Issues and Pull Requests are welcome
• Improve documentation and examples
• Share your Skills and MCPs

Plugin Ecosystem

• Officially maintained core plugins
• Community-contributed extensions
• Enterprise custom solutions

Summary

As an open-source AI agent workspace, OpenClaw provides developers with a complete AI agent development platform through its flexible multi-provider support, composable Skills architecture, and powerful developer toolchain. Whether for rapid prototyping or production-grade applications, OpenClaw has you covered.