KlavisAIKlavisAI
Sign Up

Connectto Close, Markdown2doc, Notion MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Close, Markdown2doc, Notion for enhanced automation capabilities in Klavis AI.

Get Started FreeView All MCP Servers
Close icon

Close

featured

Close is a modern CRM platform built for sales teams, providing powerful lead management, contact organization, and sales pipeline tracking to help businesses close more deals

Available Tools:

  • close_create_lead
  • close_get_lead
  • close_search_leads
  • +20 more tools
Markdown2doc icon

Markdown2doc

featured

Convert markdown text to different file formats (pdf, docx, doc, html), based on Pandoc

Available Tools:

  • convert_markdown_to_file
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

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"

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

markdown2doc_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MARKDOWN2DOC,
    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,
)

# Get tools from all MCP servers
close_tools = klavis_client.mcp_server.list_tools(
    server_url=close_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
markdown2doc_tools = klavis_client.mcp_server.list_tools(
    server_url=markdown2doc_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,
)

# Combine all tools
all_tools = []
all_tools.extend(close_tools.tools)
all_tools.extend(markdown2doc_tools.tools)
all_tools.extend(notion_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

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 Google Gemini applications with these MCP servers.

Start For Free