Connectto Airtable, Shopify, Mem0 MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Airtable, Shopify, Mem0 for enhanced automation capabilities in Klavis AI.

Airtable icon

Airtable

featured

Airtable is a cloud-based database and spreadsheet platform that combines the flexibility of a spreadsheet with the power of a database, enabling teams to organize, track, and collaborate on projects with customizable views and powerful automation features

Available Tools:

  • airtable_list_bases_info
  • airtable_list_tables_info
  • airtable_create_table
  • +8 more tools
Shopify icon

Shopify

featured

Shopify is a complete commerce platform that lets you start, grow, and manage a business. Manage products, process orders, track customers, and build your online store with powerful e-commerce tools

Available Tools:

  • shopify_list_products
  • shopify_get_product
  • shopify_create_product
  • +6 more tools
Mem0 icon

Mem0

featured

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 Together AI 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 Together AI and configure authentication settings.

3

Test & Deploy

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

Together AI + KlavisAI Integration Snippets

import os
import json
from together import Together
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

# Initialize clients
together_client = Together(api_key=os.getenv("TOGETHER_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

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

shopify_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.SHOPIFY,
    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,
)

# Get all MCP tools
airtable_tools = klavis_client.mcp_server.list_tools(
    server_url=airtable_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
shopify_tools = klavis_client.mcp_server.list_tools(
    server_url=shopify_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
mem0_tools = klavis_client.mcp_server.list_tools(
    server_url=mem0_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(airtable_tools.tools)
all_tools.extend(shopify_tools.tools)
all_tools.extend(mem0_tools.tools)

messages = [
    {"role": "system", "content": "You are a helpful AI assistant with access to multiple data sources."},
    {"role": "user", "content": user_message}
]

response = together_client.chat.completions.create(
    model="meta-llama/Llama-2-70b-chat-hf",
    messages=messages,
    tools=all_tools
)

Frequently Asked Questions

Everything you need to know about connecting to these MCP servers

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