Connectto Jira, Cloudflare, Slack MCP Servers
Create powerful collaborative AI workflows by connecting multiple MCP servers including Jira, Cloudflare, Slack for enhanced multi-agent automation capabilities in Klavis AI.
Jira
Jira is a project management and issue tracking tool developed by Atlassian
Available Tools:
- jira_search
- jira_get_issue
- jira_search_fields
- +11 more tools
Cloudflare
Cloudflare provides content delivery network services, DDoS protection, and security.
Slack
Slack is a messaging app for business that connects people to the information they need
Available Tools:
- slack_list_channels
- slack_post_message
- slack_reply_to_thread
- +6 more tools
Quick Setup Guide
Follow these steps to connect CrewAI to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Agents & Tools
Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.
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"))
jira_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.JIRA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
cloudflare_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CLOUDFLARE,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
slack_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.SLACK,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Initialize MCP tools for each server
jira_tools = MCPServerAdapter(jira_mcp_instance.server_params)
cloudflare_tools = MCPServerAdapter(cloudflare_mcp_instance.server_params)
slack_tools = MCPServerAdapter(slack_mcp_instance.server_params)
# Create specialized agents for each service
jira_agent = Agent(
role="Jira Specialist",
goal="Handle all Jira related tasks and data processing",
backstory="You are an expert in Jira operations and data analysis",
tools=jira_tools,
reasoning=True,
verbose=False
)
cloudflare_agent = Agent(
role="Cloudflare Specialist",
goal="Handle all Cloudflare related tasks and data processing",
backstory="You are an expert in Cloudflare operations and data analysis",
tools=cloudflare_tools,
reasoning=True,
verbose=False
)
slack_agent = Agent(
role="Slack Specialist",
goal="Handle all Slack related tasks and data processing",
backstory="You are an expert in Slack operations and data analysis",
tools=slack_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=jira_agent,
markdown=True
)
analysis_task = Task(
description="Analyze and synthesize the gathered data",
expected_output="Comprehensive analysis with insights and recommendations",
agent=cloudflare_agent,
markdown=True
)
# Create multi-agent crew
multi_agent_crew = Crew(
agents=[jira_agent, cloudflare_agent, slack_agent],
tasks=[research_task, analysis_task],
verbose=False,
process=Process.sequential
)
result = multi_agent_crew.kickoff()Frequently Asked Questions
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