Skip to main content
Prerequisites Before you begin, create an account and get your API Key.

​
Getting started

Connect to OpenRouter to access multiple AI models, compare model performance, and manage usage across different AI providers through AI agents.
  • API
  • UI
  • Open Source
1

Install the SDKs (optional)

pip install klavis
2

Create a Strata MCP Server with OpenRouter

from klavis import Klavis
from klavis.types import McpServerName

klavis_client = Klavis(api_key="YOUR_API_KEY")

# Create a Strata MCP server with OpenRouter
response = klavis_client.mcp_server.create_strata_server(
    servers=[McpServerName.OPENROUTER],
    user_id="user123"
)

API Reference

Full Strata API endpoints
3

Configure authentication

You can get your OpenRouter API key from the OpenRouter website.
# Set the OpenRouter API key for your instance
response = klavis_client.mcp_server.set_instance_auth(
    instance_id=openrouter_server.instance_id,
    auth_data={
        "api_key": "YOUR_OPENROUTER_API_KEY"
    }
)
🎉 Your OpenRouter MCP Server is ready! You can now use your MCP server URL with any MCP-compatible client to access multiple AI models.

​
Available Tools

With our progressive discovery approach, Klavis System is capable of enabling all tools for OpenRouter. Please use the get_tools API for more details. If you find any tool that is missing, please reach out to contact@klavis.ai.

​
Next Steps

AI Platform Integrations

Integrate Klavis MCP Servers with leading AI platforms

Integrations

Explore available MCP servers

API Reference

REST endpoints and schemas