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 icon

Zendesk

coming soon

Zendesk is a customer service software company

Klavis ReportGen icon

Klavis ReportGen

featured

Generate visually appealing JavaScript web reports from search queries with Klavis AI.

Available Tools:

  • generate_web_reports
Slack icon

Slack

featured

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 Google Gemini 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 Gemini and configure authentication settings.

3

Test & Deploy

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

Google Gemini + KlavisAI Integration Snippets

import os
import google.generativeai as genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat

# Initialize clients
genai.configure(api_key=os.getenv("GOOGLE_AI_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

# Constants
GEMINI_MODEL = "gemini-2.5-flash"
user_message = "Your query here"

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 tools from all MCP servers
zendesk_tools = klavis_client.mcp_server.list_tools(
    server_url=zendesk_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
klavis_reportgen_tools = klavis_client.mcp_server.list_tools(
    server_url=klavis_reportgen_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
slack_tools = klavis_client.mcp_server.list_tools(
    server_url=slack_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(zendesk_tools.tools)
all_tools.extend(klavis_reportgen_tools.tools)
all_tools.extend(slack_tools.tools)

model = genai.GenerativeModel(
    model_name=GEMINI_MODEL,
    tools=all_tools
)

chat = model.start_chat()
response = chat.send_message(user_message)

Frequently Asked Questions

Everything you need to know about connecting to these MCP servers

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