Connectto Asana, ClickUp, Klavis ReportGen MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Asana, ClickUp, Klavis ReportGen for enhanced automation capabilities in Klavis AI.
Asana
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
Available Tools:
- asana_create_task
- asana_get_task
- asana_search_tasks
- +16 more tools
ClickUp
ClickUp is a comprehensive project management and productivity platform that helps teams organize tasks, manage projects, and collaborate effectively with customizable workflows and powerful tracking features
Available Tools:
- clickup_get_teams
- clickup_get_workspaces
- clickup_get_spaces
- +18 more tools
Klavis ReportGen
Generate visually appealing JavaScript web reports from search queries with Klavis AI.
Available Tools:
- generate_web_reports
Quick Setup Guide
Follow these steps to connect OpenAI to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Connections
Add your desired MCP servers to OpenAI and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
OpenAI + KlavisAI Integration Snippets
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,
)
clickup_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CLICKUP,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
klavis_reportgen_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.KLAVIS_REPORTGEN,
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,
)
clickup_tools = klavis_client.mcp_server.list_tools(
server_url=clickup_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
klavis_reportgen_tools = klavis_client.mcp_server.list_tools(
server_url=klavis_reportgen_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(clickup_tools)
all_tools.extend(klavis_reportgen_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
)Frequently Asked Questions
Everything you need to know about connecting to these MCP servers
Ready to Get Started?
Join developers who are already using KlavisAI to power their OpenAI applications with these MCP servers.
Start For Free