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Prerequisites Before you begin, create an account and get your API Key.

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Getting started

Connect to Weights and Biases to track experiments, monitor model training, and collaborate on workflows from development to production through AI agents.
1

Install the SDKs (optional)

pip install klavis
2

Create a Strata MCP Server with Weights and Biases

from klavis import Klavis
from klavis.types import McpServerName

klavis_client = Klavis(api_key="YOUR_API_KEY")

# Create a Strata MCP server with Weights and Biases
response = klavis_client.mcp_server.create_strata_server(
    servers=[McpServerName.WEIGHTS_AND_BIASES],
    user_id="user123"
)
userId specifies whose connected accounts and data you are accessing in Klavis. It should be a unique id for yourself, your team, or your organization.

API Reference

Full Strata API endpoints
3

Authenticate

import webbrowser

# Open OAuth authorization page
webbrowser.open(response.oauth_urls[McpServerName.WEIGHTS_AND_BIASES])
Get your Weights and Biases API key from your Weights and Biases Developer Console.
🎉 Your Weights and Biases MCP Server is ready! Once authentication is complete, you can use your MCP server URL with any MCP-compatible client.

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Available Tools

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

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Next Steps

AI Platform Integrations

Integrate Klavis MCP Servers with leading AI platforms

Integrations

Explore available MCP servers

API Reference

REST endpoints and schemas

White-label Authentication

Customize OAuth flows with your own branding