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Connectto Stripe, Confluence, Firecrawl Deep Research MCP Servers

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

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Stripe icon

Stripe

coming soon

Stripe is a suite of payment APIs that powers commerce for online businesses

Confluence icon

Confluence

featured

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
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

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

View Documentation
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"

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

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,
)

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,
)

# Get tools from all MCP servers
stripe_tools = klavis_client.mcp_server.list_tools(
    server_url=stripe_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
confluence_tools = klavis_client.mcp_server.list_tools(
    server_url=confluence_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,
)

# Combine all tools
all_tools = []
all_tools.extend(stripe_tools.tools)
all_tools.extend(confluence_tools.tools)
all_tools.extend(firecrawl_deep_research_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

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