Connectto Linear, Perplexity MCP Servers

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

Linear icon

Linear

featured

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
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

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,
)

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
linear_tools = klavis_client.mcp_server.list_tools(
    server_url=linear_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(linear_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

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