Connectto Zendesk, Klavis ReportGen, Slack MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Zendesk, Klavis ReportGen, Slack for enhanced automation capabilities in Klavis AI.
Zendesk
Zendesk is a customer service software company
Klavis ReportGen
Generate visually appealing JavaScript web reports from search queries with Klavis AI.
Available Tools:
- generate_web_reports
Slack
Slack is a messaging app for business that connects people to the information they need
Available Tools:
- slack_list_channels
- slack_post_message
- slack_reply_to_thread
- +6 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"))
zendesk_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.ZENDESK,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
klavis_reportgen_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.KLAVIS_REPORTGEN,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
slack_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.SLACK,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get all MCP tools
zendesk_tools = klavis_client.mcp_server.list_tools(
server_url=zendesk_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
klavis_reportgen_tools = klavis_client.mcp_server.list_tools(
server_url=klavis_reportgen_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
slack_tools = klavis_client.mcp_server.list_tools(
server_url=slack_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(zendesk_tools.tools)
all_tools.extend(klavis_reportgen_tools.tools)
all_tools.extend(slack_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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