Connectto Close, Salesforce, Resend MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Close, Salesforce, Resend for enhanced automation capabilities in Klavis AI.
Close
Close is a modern CRM platform built for sales teams, providing powerful lead management, contact organization, and sales pipeline tracking to help businesses close more deals
Available Tools:
- close_create_lead
- close_get_lead
- close_search_leads
- +20 more tools
Salesforce
Salesforce is the world's leading customer relationship management (CRM) platform that helps businesses connect with customers, partners, and potential customers
Available Tools:
- salesforce_query
- salesforce_tooling_query
- salesforce_describe_object
- +2 more tools
Resend
Resend is a modern email API for sending and receiving emails programmatically
Available Tools:
- resend_send_email
- resend_create_audience
- resend_get_audience
- +12 more tools
Quick Setup Guide
Follow these steps to connect Together AI to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Connections
Add your desired MCP servers to Together AI and configure authentication settings.
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"))
close_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CLOSE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
salesforce_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.SALESFORCE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
resend_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.RESEND,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get all MCP tools
close_tools = klavis_client.mcp_server.list_tools(
server_url=close_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
salesforce_tools = klavis_client.mcp_server.list_tools(
server_url=salesforce_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
resend_tools = klavis_client.mcp_server.list_tools(
server_url=resend_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(close_tools.tools)
all_tools.extend(salesforce_tools.tools)
all_tools.extend(resend_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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