Connectto Outlook Mail, Google Docs, Firecrawl Web Search MCP Servers

Create powerful collaborative AI workflows by connecting multiple MCP servers including Outlook Mail, Google Docs, Firecrawl Web Search for enhanced multi-agent automation capabilities in Klavis AI.

Outlook Mail icon

Outlook Mail

coming soon

Outlook Mail is a web-based suite of webmail, contacts, tasks, and calendaring services from Microsoft

Google Docs icon

Google Docs

featured

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

featured

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 CrewAI to these MCP servers

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Agents & Tools

Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.

3

Deploy Your Crew

Test your multi-agent workflows and start using your enhanced collaborative AI capabilities.

CrewAI + KlavisAI Integration Snippets

import os
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType

# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

outlook_mail_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.OUTLOOK_MAIL,
    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,
)

# Initialize MCP tools for each server
outlook_mail_tools = MCPServerAdapter(outlook_mail_mcp_instance.server_params)
google_docs_tools = MCPServerAdapter(google_docs_mcp_instance.server_params)
firecrawl_web_search_tools = MCPServerAdapter(firecrawl_web_search_mcp_instance.server_params)

# Create specialized agents for each service
outlook_mail_agent = Agent(
    role="Outlook Mail Specialist",
    goal="Handle all Outlook Mail related tasks and data processing",
    backstory="You are an expert in Outlook Mail operations and data analysis",
    tools=outlook_mail_tools,
    reasoning=True,
    verbose=False
)

google_docs_agent = Agent(
    role="Google Docs Specialist",
    goal="Handle all Google Docs related tasks and data processing",
    backstory="You are an expert in Google Docs operations and data analysis",
    tools=google_docs_tools,
    reasoning=True,
    verbose=False
)

firecrawl_web_search_agent = Agent(
    role="Firecrawl Web Search Specialist",
    goal="Handle all Firecrawl Web Search related tasks and data processing",
    backstory="You are an expert in Firecrawl Web Search operations and data analysis",
    tools=firecrawl_web_search_tools,
    reasoning=True,
    verbose=False
)

# Define collaborative tasks
research_task = Task(
    description="Gather comprehensive data from all available sources",
    expected_output="Raw data and initial findings from all services",
    agent=outlook_mail_agent,
    markdown=True
)

analysis_task = Task(
    description="Analyze and synthesize the gathered data",
    expected_output="Comprehensive analysis with insights and recommendations",
    agent=google_docs_agent,
    markdown=True
)

# Create multi-agent crew
multi_agent_crew = Crew(
    agents=[outlook_mail_agent, google_docs_agent, firecrawl_web_search_agent],
    tasks=[research_task, analysis_task],
    verbose=False,
    process=Process.sequential
)

result = multi_agent_crew.kickoff()

Frequently Asked Questions

Everything you need to know about connecting CrewAI to these MCP servers

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