Connectto Markdown2doc, Notion, Klavis ReportGen MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Markdown2doc, Notion, Klavis ReportGen for enhanced automation capabilities in Klavis AI.
Markdown2doc
Convert markdown text to different file formats (pdf, docx, doc, html), based on Pandoc
Available Tools:
- convert_markdown_to_file
Notion
Notion is a collaborative productivity and note-taking application
Available Tools:
- notion_get_user
- notion_get_users
- notion_get_self
- +10 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 Google Gemini 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 Gemini and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
Google Gemini + KlavisAI Integration Snippets
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"
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,
)
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
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,
)
klavis_reportgen_tools = klavis_client.mcp_server.list_tools(
server_url=klavis_reportgen_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
# Combine all tools
all_tools = []
all_tools.extend(markdown2doc_tools.tools)
all_tools.extend(notion_tools.tools)
all_tools.extend(klavis_reportgen_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
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