AI Assistant Server Setup

You can install an AI assistant on your server using open-source frameworks like OpenClaw or Vezlo, or enterprise solutions such as JetBrains AI or Azure DevOps MCP Server, depending on your requirements.

Choosing the Right A

I AssistantOpenClaw: An open-source AI assistant framework for Linux servers that allows full control over your data and integration with models like GPT-4 and Claude. Ideal for self-hosted deployments with custom workflows.

Vezlo A

I Assistant Server: A production-ready Node.js/TypeScript API server with Docker deployment, database migrations, and interactive setup wizard for easy configuration.

Jet

Brains A

I Assistant: A plugin for JetBrains IDEs that can run locally with organizational subscriptions, suitable for developers who want AI assistance integrated into their IDE.

Azure Dev

Ops MC

P Server: Provides secure, local access to Azure DevOps data for AI assistants, enabling project-specific insights without sending data to the cloud.

General Installation Steps

Prepare Your Server

Ensure your server meets the system requirements (e.g., Node.js 20+ for Azure MCP Server, Node.js 22+ for OpenClaw). Install necessary dependencies such as Docker, database engines (PostgreSQL, Supabase), and any required libraries.

Download and Configure

For Open

Claw, you can run the onboarding script: openclaw onboard --install-daemon for a quick setup. For Vezlo, clone the repository or install locally, then run the interactive setup wizard to configure environment variables, database connections, and API keys.

For Jet

Brains A

I, install the plugin via the AI Chat tool window, JetBrains AI widget, or Marketplace, then verify your subscription.

For Azure MC

P Server, follow the environment-specific instructions to connect your AI assistant in agent mode to your Azure DevOps organization.

Database and API Configuration

Set up your database tables using automated scripts or manual SQL commands.

Configure AP

I keys for AI models (OpenAI, Claude, etc.) and any optional features like rate limiting or CORS.

Start the Server

Use the provided CLI or Docker commands to start the server. Validate the setup by checking logs and ensuring the AI assistant responds to queries.

Optional Enhancements

Integrate messaging platforms like WhatsApp or Telegram (OpenClaw). Add custom skills or workflows tailored to your business needs. Enable enterprise-grade security and monitoring. Tips for a Successful DeploymentAlways backup your configuration and database before major updates. Test the A I assistant in a staging environment before production deployment. Monitor resource usage, especially for large language models, as they can be resource-intensive. Consider subscription tiers or licensing for enterprise solutions to unlock advanced features. By following these steps, you can deploy a fully functional AI assistant on your server, whether for personal use, development, or enterprise integration.