Connectto LinkedIn, Firecrawl Deep Research, Motion MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including LinkedIn, Firecrawl Deep Research, Motion with Claude's advanced reasoning capabilities in Klavis AI.
LinkedIn is a business and employment-oriented online service
Firecrawl Deep Research
A personal research assistant that analyze sources across the web, based on Firecrawl
Available Tools:
- firecrawl_deep_research
Motion
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 Claude to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform and get your API keys.
Configure Connections
Add your desired MCP servers to Claude and configure authentication settings with your Anthropic API key.
Test & Deploy
Verify your connections work correctly with Claude's function calling and start using your enhanced AI capabilities.
Claude + KlavisAI Integration Snippets
import os
import json
from anthropic import Anthropic
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
anthropic_client = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
# Constants
CLAUDE_MODEL = "claude-3-5-sonnet-20241022"
user_message = "Your message here"
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,
)
firecrawl_deep_research_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.FIRECRAWL_DEEP_RESEARCH,
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.ANTHROPIC,
)
firecrawl_deep_research_tools = klavis_client.mcp_server.list_tools(
server_url=firecrawl_deep_research_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.ANTHROPIC,
)
motion_tools = klavis_client.mcp_server.list_tools(
server_url=motion_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.ANTHROPIC,
)
# Combine all tools
all_tools = []
all_tools.extend(linkedin_tools.tools)
all_tools.extend(firecrawl_deep_research_tools.tools)
all_tools.extend(motion_tools.tools)
messages = [
{"role": "user", "content": user_message}
]
response = anthropic_client.messages.create(
model=CLAUDE_MODEL,
max_tokens=4000,
messages=messages,
tools=all_tools
)Frequently Asked Questions
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