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Connectto Doc2markdown, Firecrawl Web Search, OpenRouter MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Doc2markdown, Firecrawl Web Search, OpenRouter for enhanced automation capabilities in Klavis AI.

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Doc2markdown icon

Doc2markdown

featured

Convert any file to markdown using markitdown

Available Tools:

  • convert_document_to_markdown
Firecrawl Web Search icon

Firecrawl Web Search

featured

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

Available Tools:

  • firecrawl_scrape
  • firecrawl_map
  • firecrawl_crawl
  • +6 more tools
OpenRouter icon

OpenRouter

featured

Access to multiple AI models through a unified API. Generate chat completions, compare model performance, manage usage and costs, get model recommendations, and analyze model capabilities across various providers like OpenAI, Anthropic, Meta, Google, and more

Available Tools:

  • openrouter_list_models
  • openrouter_search_models
  • openrouter_get_model_pricing
  • +11 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
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"

doc2markdown_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.DOC2MARKDOWN,
    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,
)

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

# Get tools from all MCP servers
doc2markdown_tools = klavis_client.mcp_server.list_tools(
    server_url=doc2markdown_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,
)
openrouter_tools = klavis_client.mcp_server.list_tools(
    server_url=openrouter_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(doc2markdown_tools.tools)
all_tools.extend(firecrawl_web_search_tools.tools)
all_tools.extend(openrouter_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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