Azure + Klavis AI: Complete MCP Integration

Azure is a MCP server that The Azure MCP Server gives MCP Clients access to key Azure services and tools like Azure Storage, Cosmos DB, the Azure CLI, and more..

When integrated with Klavis AI, you can:

• Access Azure functionality through Klavis AI

This guide provides step-by-step instructions to set up Azure in Klavis AI, including configuration, examples, and troubleshooting.

What You'll Achieve

After completing this setup:

• Azure will be fully integrated and operational
• You can use Azure tools directly in Klavis AI
• All Azure capabilities will be available for your workflows

Prerequisites

Before starting, ensure you have:

• Klavis AI installed and configured
• Compatible operating system (Cloud (klavis.ai), Self-Hosted (Docker), Python SDK, TypeScript SDK)

Installation

Step 1: Install Azure

Configuration

Step 2: Configure Klavis AI

1. Open Klavis AI settings
2. Navigate to MCP server configuration
3. Add Azure server with appropriate settings
4. Save and restart if needed

Examples

Once configured, you can use Azure in Klavis AI:

Testing Your Setup

1. Launch Klavis AI
2. Verify Azure is available in the tools list
3. Test basic Azure functionality

Troubleshooting

Common Issues

API Authentication Failed

Symptoms: 401 Unauthorized errors, Invalid API key message

Cause: Missing or incorrect API key

Solution:

• Verify API key is correctly copied from klavis.ai dashboard
• Check API key is set in environment variable or code
• Ensure API key has not expired
• Regenerate API key if necessary

OAuth Authorization Errors

Symptoms: OAuth redirect failures, Authentication loop, Token refresh errors

Cause: OAuth credentials not configured or expired

Solution:

• Complete OAuth authorization flow for required services
• Check redirect URLs are correctly configured
• Verify OAuth app credentials in service provider settings
• Contact Klavis support for OAuth troubleshooting

Tool Call Failures

Symptoms: Tool not found errors, Execution timeouts, Rate limit errors

Cause: Tool not properly configured or service rate limits exceeded

Solution:

• Verify tool name matches available tools list
• Check service-specific rate limits and quotas
• Ensure required parameters are provided correctly
• Review Klavis API logs for detailed error messages

Context Window Overload

Symptoms: Too many tools error, Context length exceeded, Slow responses

Cause: Too many tools exposed to AI agent at once

Solution:

• Use Strata Progressive Discovery to expose tools hierarchically
• Reduce number of simultaneous MCP servers in Strata configuration
• Filter tools based on current task context
• Enable intelligent tool filtering in Strata settings

Docker Deployment Issues

Symptoms: Container fails to start, Port conflicts, Connection refused

Cause: Docker configuration or port binding errors

Solution:

• Ensure Docker is installed and running
• Check port 5000 is not already in use (or change port mapping)
• Verify Docker image pulled successfully
• Check container logs: docker logs <container-id>

Azure not appearing in Klavis AI

Symptoms: Server not listed, Tools not available

Cause: Configuration or installation issue

Solution:

• Verify configuration syntax
• Check Azure installation
• Restart Klavis AI
• Check logs for error messages

Next Steps

Now that Azure is integrated with Klavis AI:

• Explore all Azure capabilities through Klavis AI
• Check out other MCP servers that work with Klavis AI
• Join the MCP community for tips and support
• Consider contributing to Azure development

Need Help?

• Search for Azure documentation
• Check the Klavis AI MCP guide
• Join the MCP community discussions