Awesome OpenClaw is a self-hosted AI agent framework that lets you manage and run your personal AI assistant locally across multiple messaging platforms. With MCP support, this server exposes capabilities to configure and extend the agent’s behavior, tool integrations, and memory/context management, allowing you to compose more autonomous workflows. The CLI flow centers around onboarding your agent, selecting an AI provider (Anthropic Claude, OpenAI GPT, or a local model via Ollama), and connecting messaging platforms such as Telegram, WhatsApp, or Discord. The included MCP integration enables extended agentic capabilities, so you can add custom skills, plugins, and multi-provider model support to tailor how the agent reasons and acts. You can leverage the built-in web dashboard to monitor integrations, adjust memory persistence, and fine-tune tool usage without heavy CLI interaction. This MCP-enabled setup is ideal if you want a private, self-hosted AI assistant that can operate with a broad ecosystem of tools and providers while staying under your control.

Prerequisites:

• Node.js 14+ and npm (or a compatible Node.js environment)
• Internet connectivity to fetch the MCP package

Install and run:

1. Ensure Node.js and npm are installed. Verify with: node -v npm -v

2. Install the OpenClaw MCP-enabled CLI package globally (via npx for one-off usage): npx -y openclaw

   If you prefer a persistent install, you can also run:

   npm install -g openclaw@latest

3. Run the onboarding flow to set up your agent: openclaw onboard --install-daemon

4. Follow the interactive prompts:

   • Choose your AI provider (Anthropic Claude, OpenAI GPT, or local Ollama)
   • Connect a messaging platform (Telegram recommended for beginners)
   • Start the agent and access the dashboard at http://localhost:18789/

Notes:

• The onboarding flow configures MCP-enabled capabilities and prepares the local environment for agent operation.
• If you already have OpenClaw installed, you can activate MCP features by running onboard and selecting the appropriate options during setup.

Tips and caveats:

• The MCP integration enables extended agent capabilities via modular skills/plugins; explore ClawHub and the skills catalog to expand functionality.
• Memory persistence is designed to remember context across sessions; ensure your storage backend (local disk) is accessible and has sufficient space.
• If you run into port conflicts, you can customize the dashboard port in the onboarding options or in the config file after setup.
• For non-GUI environments, you can still interact with the agent via the onboard CLI or API endpoints exposed by the web dashboard.
• When using external providers (OpenAI/Anthropic/Google Gemini), ensure API keys are configured securely (environment variables or secret management).
• MCP support means you can author and deploy custom skills that leverage model/context capabilities to perform more autonomous tasks.