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Connectto Postgres, Google Docs, Firecrawl Web Search MCP Servers

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

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Postgres icon

Postgres

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PostgreSQL is a powerful, open source object-relational database system

Available Tools:

  • query
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"

postgres_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.POSTGRES,
    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
postgres_tools = klavis_client.mcp_server.list_tools(
    server_url=postgres_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(postgres_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

Everything you need to know about connecting to these MCP servers

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