Connectto Box, SendGrid MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Box, SendGrid for enhanced automation capabilities in Klavis AI.

Box icon

Box

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Box is a cloud content management and file sharing platform. Upload, download, share files, manage folders, and collaborate on documents via OpenAPI integration

SendGrid icon

SendGrid

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SendGrid is a cloud-based email delivery platform. Send transactional and marketing emails, manage contacts, track email analytics, handle bounces, and manage templates via OpenAPI integration

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"))

box_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.BOX,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

sendgrid_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.SENDGRID,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

mcp_client = MultiServerMCPClient({
    "box": {
        "transport": "streamable_http",
        "url": box_mcp_instance.server_url
    },
    "sendgrid": {
        "transport": "streamable_http",
        "url": sendgrid_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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