Jira Integration

uv add crewai-tools

from crewai import Agent, Task, Crew
from crewai_tools import CrewaiEnterpriseTools

# Get enterprise tools (Jira tools will be included)
enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token"
)

# Create an agent with Jira capabilities
jira_agent = Agent(
    role="Issue Manager",
    goal="Manage Jira issues and track project progress efficiently",
    backstory="An AI assistant specialized in issue tracking and project management.",
    tools=[enterprise_tools]
)

# Task to create a bug report
create_bug_task = Task(
    description="Create a bug report for the login functionality with high priority and assign it to the development team",
    agent=jira_agent,
    expected_output="Bug report created successfully with issue key"
)

# Run the task
crew = Crew(
    agents=[jira_agent],
    tasks=[create_bug_task]
)

crew.kickoff()

from crewai_tools import CrewaiEnterpriseTools

# Get only specific Jira tools
enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token",
    actions_list=["jira_create_issue", "jira_update_issue", "jira_search_by_jql"]
)

issue_coordinator = Agent(
    role="Issue Coordinator",
    goal="Create and manage Jira issues efficiently",
    backstory="An AI assistant that focuses on issue creation and management.",
    tools=enterprise_tools
)

# Task to manage issue workflow
issue_workflow = Task(
    description="Create a feature request issue and update the status of related issues",
    agent=issue_coordinator,
    expected_output="Feature request created and related issues updated"
)

crew = Crew(
    agents=[issue_coordinator],
    tasks=[issue_workflow]
)

crew.kickoff()

from crewai import Agent, Task, Crew
from crewai_tools import CrewaiEnterpriseTools

enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token"
)

project_analyst = Agent(
    role="Project Analyst",
    goal="Analyze project data and generate insights from Jira",
    backstory="An experienced project analyst who extracts insights from project management data.",
    tools=[enterprise_tools]
)

# Task to analyze project status
analysis_task = Task(
    description="""
    1. Get all projects and their issue types
    2. Search for all open issues across projects
    3. Analyze issue distribution by status and assignee
    4. Create a summary report issue with findings
    """,
    agent=project_analyst,
    expected_output="Project analysis completed with summary report created"
)

crew = Crew(
    agents=[project_analyst],
    tasks=[analysis_task]
)

crew.kickoff()

from crewai import Agent, Task, Crew
from crewai_tools import CrewaiEnterpriseTools

enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token"
)

automation_manager = Agent(
    role="Automation Manager",
    goal="Automate issue management and workflow processes",
    backstory="An AI assistant that automates repetitive issue management tasks.",
    tools=[enterprise_tools]
)

# Task to automate issue management
automation_task = Task(
    description="""
    1. Search for all unassigned issues using JQL
    2. Get available assignees for each project
    3. Automatically assign issues based on workload and expertise
    4. Update issue priorities based on age and type
    5. Create weekly sprint planning issues
    """,
    agent=automation_manager,
    expected_output="Issues automatically assigned and sprint planning issues created"
)

crew = Crew(
    agents=[automation_manager],
    tasks=[automation_task]
)

crew.kickoff()

from crewai import Agent, Task, Crew
from crewai_tools import CrewaiEnterpriseTools

enterprise_tools = CrewaiEnterpriseTools(
    enterprise_token="your_enterprise_token"
)

schema_specialist = Agent(
    role="Schema Specialist",
    goal="Handle complex Jira operations using dynamic schemas",
    backstory="An AI assistant that can work with dynamic Jira schemas and custom issue types.",
    tools=[enterprise_tools]
)

# Task using schema-based operations
schema_task = Task(
    description="""
    1. Get all projects and their custom issue types
    2. For each custom issue type, describe the action schema
    3. Create issues using the dynamic schema for complex custom fields
    4. Update issues with custom field values based on business rules
    """,
    agent=schema_specialist,
    expected_output="Custom issues created and updated using dynamic schemas"
)

crew = Crew(
    agents=[schema_specialist],
    tasks=[schema_task]
)

crew.kickoff()