Connectto ClickUp, Firecrawl Deep Research, Google Jobs MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including ClickUp, Firecrawl Deep Research, Google Jobs for enhanced automation capabilities in Klavis AI.

ClickUp icon

ClickUp

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ClickUp is a comprehensive project management and productivity platform that helps teams organize tasks, manage projects, and collaborate effectively with customizable workflows and powerful tracking features

Available Tools:

  • clickup_get_teams
  • clickup_get_workspaces
  • clickup_get_spaces
  • +18 more tools
Firecrawl Deep Research icon

Firecrawl Deep Research

featured

A personal research assistant that analyze sources across the web, based on Firecrawl

Available Tools:

  • firecrawl_deep_research
Google Jobs icon

Google Jobs

featured

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

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
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"

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

firecrawl_deep_research_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.FIRECRAWL_DEEP_RESEARCH,
    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
clickup_tools = klavis_client.mcp_server.list_tools(
    server_url=clickup_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
firecrawl_deep_research_tools = klavis_client.mcp_server.list_tools(
    server_url=firecrawl_deep_research_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(clickup_tools.tools)
all_tools.extend(firecrawl_deep_research_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

Everything you need to know about connecting to these MCP servers

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