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Connectto Gong, Google Docs, Firecrawl Web Search MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Gong, Google Docs, Firecrawl Web Search for enhanced automation capabilities in Klavis AI.

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Gong icon

Gong

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Gong is a revenue intelligence platform that captures and analyzes all revenue-related interactions to help sales teams close more deals. It provides conversation analytics, deal insights, and sales performance tracking through call recordings and transcripts

Available Tools:

  • gong_get_transcripts_by_user
  • gong_get_extensive_data
  • gong_get_call_transcripts
  • +2 more tools
Google Docs icon

Google Docs

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Google Docs is a word processor included as part of the free, web-based Google Docs Editors suite

Available Tools:

  • google_docs_get_document_by_id
  • google_docs_get_all_documents
  • google_docs_insert_text_at_end
  • +2 more tools
Firecrawl Web Search icon

Firecrawl Web Search

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Advanced web crawling, scraping, and search capabilities powered by Firecrawl

Available Tools:

  • firecrawl_scrape
  • firecrawl_map
  • firecrawl_crawl
  • +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

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"

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

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

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

# Get tools from all MCP servers
gong_tools = klavis_client.mcp_server.list_tools(
    server_url=gong_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
google_docs_tools = klavis_client.mcp_server.list_tools(
    server_url=google_docs_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
firecrawl_web_search_tools = klavis_client.mcp_server.list_tools(
    server_url=firecrawl_web_search_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(gong_tools.tools)
all_tools.extend(google_docs_tools.tools)
all_tools.extend(firecrawl_web_search_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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