Connectto Linear, Notion, Figma MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Linear, Notion, Figma for enhanced automation capabilities in Klavis AI.
Linear
Linear is a modern issue tracking and project management tool designed for high-performance teams to build better software faster
Available Tools:
- linear_get_teams
- linear_get_issues
- linear_get_issue_by_id
- +9 more tools
Notion
Notion is a collaborative productivity and note-taking application
Available Tools:
- notion_get_user
- notion_get_users
- notion_get_self
- +10 more tools
Figma
Figma is a collaborative interface design tool for web and mobile applications.
Quick Setup Guide
Follow these steps to connect Google Gemini to these MCP servers
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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"
linear_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.LINEAR,
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,
)
figma_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.FIGMA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get tools from all MCP servers
linear_tools = klavis_client.mcp_server.list_tools(
server_url=linear_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,
)
figma_tools = klavis_client.mcp_server.list_tools(
server_url=figma_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
# Combine all tools
all_tools = []
all_tools.extend(linear_tools.tools)
all_tools.extend(notion_tools.tools)
all_tools.extend(figma_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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