Connectto Firecrawl Deep Research, Heygen, Mem0 MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Firecrawl Deep Research, Heygen, Mem0 for enhanced automation capabilities in Klavis AI.

Firecrawl Deep Research icon

Firecrawl Deep Research

featured

A personal research assistant that analyze sources across the web, based on Firecrawl

Available Tools:

  • firecrawl_deep_research
Heygen icon

Heygen

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HeyGen is an AI video generation platform that creates professional videos with AI avatars and voices. Generate avatar videos with customizable text, voices, and avatars, manage your video library, and track generation status

Available Tools:

  • heygen_get_remaining_credits
  • heygen_get_voices
  • heygen_get_voice_locales
  • +7 more tools
Mem0 icon

Mem0

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Mem0 is an intelligent memory layer for AI applications that provides long-term memory storage and retrieval. Store code snippets, implementation details, and programming knowledge for seamless context retention across conversations

Available Tools:

  • mem0_add_memory
  • mem0_get_all_memories
  • mem0_search_memories
  • +2 more tools

Quick Setup Guide

Follow these steps to connect LangChain 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 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"))

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,
)

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

mem0_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MEM0,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

mcp_client = MultiServerMCPClient({
    "firecrawl deep research": {
        "transport": "streamable_http",
        "url": firecrawl_deep_research_mcp_instance.server_url
    },
    "heygen": {
        "transport": "streamable_http",
        "url": heygen_mcp_instance.server_url
    },
    "mem0": {
        "transport": "streamable_http",
        "url": mem0_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 these MCP servers

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