Connectto LinkedIn, Perplexity, Motion MCP Servers

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

LinkedIn icon

LinkedIn

coming soon

LinkedIn is a business and employment-oriented online service

Perplexity icon

Perplexity

coming soon

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

Motion icon

Motion

featured

Motion is an intelligent project management and calendar application that automatically schedules your tasks, meetings, and projects to optimize your productivity and help you focus on what matters most

Available Tools:

  • motion_get_workspaces
  • motion_get_users
  • motion_get_my_user
  • +11 more tools

Quick Setup Guide

Follow these steps to connect OpenAI 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 OpenAI and configure authentication settings.

3

Test & Deploy

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

OpenAI + KlavisAI Integration Snippets

import json
import os
from openai import OpenAI
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

# Initialize clients
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

# Constants
OPENAI_MODEL = "gpt-4o-mini"

linkedin_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.LINKEDIN,
    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,
)

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

# Get tools from all MCP servers
linkedin_tools = klavis_client.mcp_server.list_tools(
    server_url=linkedin_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
perplexity_tools = klavis_client.mcp_server.list_tools(
    server_url=perplexity_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
motion_tools = klavis_client.mcp_server.list_tools(
    server_url=motion_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(linkedin_tools)
all_tools.extend(perplexity_tools)
all_tools.extend(motion_tools)

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": user_message}
]
        
response = openai_client.chat.completions.create(
    model=OPENAI_MODEL,
    messages=messages,
    tools=all_tools if all_tools else None
)

Frequently Asked Questions

Everything you need to know about connecting to these MCP servers

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