Connectto Markdown2doc MCP Server

Seamlessly integrate your LangChain and AI applications with Markdown2doc using Klavis AI's comprehensive MCP server connection guide.

Markdown2doc icon

Markdown2doc

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Convert markdown text to different file formats (pdf, docx, doc, html), based on Pandoc

Available Tools:

  • convert_markdown_to_file

Quick Setup Guide

Follow these steps to connect LangChain to this MCP server

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Connections

Add the MCP server to LangChain and configure authentication settings.

3

Test & Deploy

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

LangChain + KlavisAI Integration Snippets

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"))

markdown2doc_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MARKDOWN2DOC,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

mcp_client = MultiServerMCPClient({
    "markdown2doc": {
        "transport": "streamable_http",
        "url": markdown2doc_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"}]
}))

Frequently Asked Questions

Everything you need to know about connecting to this MCP server

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