Create powerful AI workflows by connecting multiple MCP servers including Asana, OneDrive, Google Docs for enhanced automation capabilities in Klavis AI.
Asana is a web and mobile application designed to help teams organize, track, and manage their work. It provides project management tools, task assignment, collaboration features, and progress tracking to boost team productivity
OneDrive is a file hosting service and synchronization service operated by Microsoft
Google Docs is a word processor included as part of the free, web-based Google Docs Editors suite
Follow these steps to connect OpenAI to these MCP servers
Sign up for KlavisAI to access our MCP server management platform.
Add your desired MCP servers to OpenAI and configure authentication settings.
Verify your connections work correctly and start using your enhanced AI capabilities.
import json
import os
from openai import OpenAI
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
# Constants
OPENAI_MODEL = "gpt-4o-mini"
asana_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.ASANA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
onedrive_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.ONEDRIVE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
google_docs_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_DOCS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get tools from all MCP servers
asana_tools = klavis_client.mcp_server.list_tools(
server_url=asana_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
onedrive_tools = klavis_client.mcp_server.list_tools(
server_url=onedrive_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
google_docs_tools = klavis_client.mcp_server.list_tools(
server_url=google_docs_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(asana_tools)
all_tools.extend(onedrive_tools)
all_tools.extend(google_docs_tools)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": user_message}
]
response = openai_client.chat.completions.create(
model=OPENAI_MODEL,
messages=messages,
tools=all_tools if all_tools else None
)
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