Create powerful AI workflows by connecting multiple MCP servers including WordPress, Doc2markdown, Motion for enhanced automation capabilities in Klavis AI.
WordPress is an open-source content management system for building websites and blogs
Convert any file to markdown using markitdown
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
Follow these steps to connect LangChain to these MCP servers
Sign up for KlavisAI to access our MCP server management platform.
Add your desired MCP servers to LangChain and configure authentication settings.
Verify your connections work correctly and start using your enhanced AI capabilities.
import os
import asyncio
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
llm = ChatOpenAI(model="gpt-4o-mini", api_key=os.getenv("OPENAI_API_KEY"))
wordpress_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.WORDPRESS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
doc2markdown_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.DOC2MARKDOWN,
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,
)
mcp_client = MultiServerMCPClient({
"wordpress": {
"transport": "streamable_http",
"url": wordpress_mcp_instance.server_url
},
"doc2markdown": {
"transport": "streamable_http",
"url": doc2markdown_mcp_instance.server_url
},
"motion": {
"transport": "streamable_http",
"url": motion_mcp_instance.server_url
}
})
tools = asyncio.run(mcp_client.get_tools())
agent = create_react_agent(
model=llm,
tools=tools,
)
response = asyncio.run(agent.ainvoke({
"messages": [{"role": "user", "content": "Your query here"}]
}))
Everything you need to know about connecting to these MCP servers
Join developers who are already using KlavisAI to power their LangChain applications with these MCP servers.
Start For Free