Connectto Mem0, Cal.com MCP Servers

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

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
Cal.com icon

Cal.com

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Cal.com is an open-source scheduling platform that helps you schedule meetings without the back-and-forth emails. Manage event types, bookings, availability, and integrate with calendars for seamless appointment scheduling

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"))

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

cal.com_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.CAL.COM,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Get all MCP tools
mem0_tools = klavis_client.mcp_server.list_tools(
    server_url=mem0_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
cal.com_tools = klavis_client.mcp_server.list_tools(
    server_url=cal.com_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(mem0_tools.tools)
all_tools.extend(cal.com_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

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