Connectto Freshdesk, Exa, Monday MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Freshdesk, Exa, Monday for enhanced automation capabilities in Klavis AI.

Freshdesk icon

Freshdesk

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Freshdesk is a cloud-based customer support software that helps businesses manage customer inquiries across multiple channels. Create and manage tickets, contacts, companies, and agents with powerful automation and collaboration features

Available Tools:

  • freshdesk_create_ticket
  • freshdesk_get_ticket_by_id
  • freshdesk_update_ticket
  • +52 more tools
Exa icon

Exa

featured

Exa is an AI-powered search engine designed for AI applications. Use neural search to understand meaning and context, find similar content, get direct answers with citations, and conduct comprehensive research with structured analysis

Available Tools:

  • exa_search
  • exa_get_contents
  • exa_find_similar
  • +2 more tools
Monday icon

Monday

featured

Monday.com is a work operating system that powers teams to run projects and workflows with confidence. Create boards, manage items, customize columns, organize groups, and collaborate with team members in a visual workspace

Available Tools:

  • monday_get_users_by_name
  • monday_get_boards
  • monday_create_board
  • +9 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"))

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

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

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

# Get all MCP tools
freshdesk_tools = klavis_client.mcp_server.list_tools(
    server_url=freshdesk_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
exa_tools = klavis_client.mcp_server.list_tools(
    server_url=exa_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
monday_tools = klavis_client.mcp_server.list_tools(
    server_url=monday_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(freshdesk_tools.tools)
all_tools.extend(exa_tools.tools)
all_tools.extend(monday_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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