Connectto Confluence, Tavily, Google Jobs MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Confluence, Tavily, Google Jobs for enhanced automation capabilities in Klavis AI.
Confluence
Confluence is a team workspace where knowledge and collaboration meet
Available Tools:
- confluence_create_page
- confluence_get_page
- confluence_get_pages_by_id
- +11 more tools
Tavily
Tavily is an AI-powered search API designed for LLMs and AI agents. Get real-time web search results, extract content from URLs, crawl websites, and generate site maps with advanced filtering and parsing capabilities
Available Tools:
- tavily_search
- tavily_extract
- tavily_crawl
- +1 more tools
Google Jobs
Google Jobs is a comprehensive job search platform that aggregates listings from across the web. Search for jobs by location, company, employment type, and more, with detailed information about requirements, benefits, and application processes
Available Tools:
- google_jobs_search
- google_jobs_get_details
- google_jobs_search_by_company
- +2 more tools
Quick Setup Guide
Follow these steps to connect Google Gemini 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 Gemini and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
Google Gemini + KlavisAI Integration Snippets
import os
from google import genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
client = genai.Client(api_key=os.getenv("GOOGLE_API_KEY"))
user_message = "Your query here"
confluence_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CONFLUENCE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
tavily_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.TAVILY,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
google_jobs_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_JOBS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get tools from all MCP servers
confluence_tools = klavis_client.mcp_server.list_tools(
server_url=confluence_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
tavily_tools = klavis_client.mcp_server.list_tools(
server_url=tavily_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
google_jobs_tools = klavis_client.mcp_server.list_tools(
server_url=google_jobs_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
# Combine all tools
all_tools = []
all_tools.extend(confluence_tools.tools)
all_tools.extend(tavily_tools.tools)
all_tools.extend(google_jobs_tools.tools)
response = client.models.generate_content(
model="gemini-2.5-flash",
contents=user_message,
config=genai.types.GenerateContentConfig(
tools=all_tools,
),
)Frequently Asked Questions
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