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Connectto Asana, Notion, Perplexity MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Asana, Notion, Perplexity for enhanced automation capabilities in Klavis AI.

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Asana icon

Asana

featured

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
Notion icon

Notion

featured

Notion is a collaborative productivity and note-taking application

Available Tools:

  • notion_get_user
  • notion_get_users
  • notion_get_self
  • +10 more tools
Perplexity icon

Perplexity

coming soon

Perplexity is an AI research assistant that provides accurate answers and cites sources

Quick Setup Guide

Follow these steps to connect Google Gemini to these MCP servers

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Connections

Add your desired MCP servers to Gemini and configure authentication settings.

3

Test & Deploy

Verify your connections work correctly and start using your enhanced AI capabilities.

Google Gemini + KlavisAI Integration Snippets

View Documentation
import os
import google.generativeai as genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

# Initialize clients
genai.configure(api_key=os.getenv("GOOGLE_AI_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

# Constants
GEMINI_MODEL = "gemini-2.5-flash"
user_message = "Your query here"

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,
)

notion_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.NOTION,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

perplexity_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.PERPLEXITY,
    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.GEMINI,
)
notion_tools = klavis_client.mcp_server.list_tools(
    server_url=notion_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
perplexity_tools = klavis_client.mcp_server.list_tools(
    server_url=perplexity_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(asana_tools.tools)
all_tools.extend(notion_tools.tools)
all_tools.extend(perplexity_tools.tools)

model = genai.GenerativeModel(
    model_name=GEMINI_MODEL,
    tools=all_tools
)

chat = model.start_chat()
response = chat.send_message(user_message)

Frequently Asked Questions

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