How to integrate Jira MCP with CrewAI

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Introduction

This guide walks you through connecting Jira to CrewAI using the Composio tool router. By the end, you'll have a working Jira agent that can create a new bug in project alpha, assign issue jira-102 to sarah lee, add comment to ticket jira-207 with update through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Jira account through Composio's Jira MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Jira with

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Jira connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Jira
  • Build a conversational loop where your agent can execute Jira operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Jira MCP server, and what's possible with it?

The Jira MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Jira account. It provides structured and secure access to your Jira projects, so your agent can perform actions like creating issues, managing sprints, commenting on tasks, assigning work, and tracking releases on your behalf.

  • Automated issue creation and tracking: Let your agent create new bugs, tasks, or stories, and keep tabs on issues across your Jira projects.
  • Collaborative commenting and updates: Have your agent add rich-text comments or attachments to issues, keeping team communication seamless and up to date.
  • Effortless assignment and watcher management: Easily assign issues to teammates or add watchers, ensuring everyone stays in the loop and accountable.
  • Sprint and release planning: Empower your agent to create sprints, manage boards, and organize project milestones or versions for agile teams.
  • Issue linking and bulk operations: Direct your agent to link related issues or perform bulk creation of tasks, streamlining project workflows and dependencies.

Supported Tools & Triggers

Tools
Triggers
Add AttachmentUploads and attaches a file to a Jira issue.
Add CommentAdds a comment using Atlassian Document Format (ADF) for rich text to an existing Jira issue.
Add Users to Project RoleAdds users and optionally groups to a project role.
Add User to GroupAdds a user to a Jira group.
Add Watcher to IssueAdds a user to an issue's watcher list by account ID.
Add WorklogTool to add a worklog entry to a Jira issue.
Analyse Jira ExpressionAnalyses Jira expressions for syntax validation, type checking, and complexity analysis.
Assign IssueAssigns a Jira issue to a user, default assignee, or unassigns; supports email/name lookup.
Bulk Create IssuesCreates multiple Jira issues (up to 50 per call) with full feature support including markdown, assignee resolution, and priority handling.
Check User PermissionsCheck user permissions for global and project-level operations in Jira.
Create GroupCreates a new group in Jira with the specified name.
Create IssueCreates a new Jira issue (e.
Link IssuesLinks two Jira issues using a specified link type with optional comment.
Get JQL Autocomplete DataRetrieves JQL autocomplete reference data including reserved words, field names, and function names.
Create ProjectCreates a new Jira project with required lead, template, and type configuration.
Create SprintCreates a new sprint on a Jira board with optional start/end dates and goal.
Create VersionCreates a new version for releases or milestones in a Jira project.
Delete CommentDeletes a specific comment from a Jira issue using its ID and the issue's ID/key; requires user permission to delete comments on the issue.
Delete IssuePermanently and irreversibly deletes a Jira issue by its ID or key.
Delete VersionDeletes a Jira version and optionally reassigns its issues.
Delete WorklogDeletes a worklog from a Jira issue with estimate adjustment options.
Edit IssueUpdates an existing Jira issue with field values and operations.
Evaluate Jira ExpressionTool to evaluate Jira expressions using the enhanced search API.
Bulk Fetch IssuesTool to bulk fetch multiple Jira issues by their IDs or keys (max 100 per call).
Find Users 2Tool to find users in Jira by query string, account ID, or property search.
Find Users For PickerFind users for picker components by matching query against user attributes like display name and email.
Get All GroupsRetrieves all groups from the Jira instance with pagination support.
Get All Issue Type SchemesRetrieves all Jira issue type schemes with optional filtering and pagination.
Get all projectsRetrieves all visible projects using the modern paginated Jira API with server-side filtering and pagination support.
Get Issue StatusesRetrieves all issue statuses associated with workflows from Jira.
Get All UsersRetrieves all users from the Jira instance including active, inactive, app accounts, and system accounts, with pagination support.
Get AttachmentRetrieves the binary content of a Jira attachment by ID.
Get Attachment MetaTool to retrieve Jira attachment settings including upload limits and enabled status.
Get CommentRetrieves a specific comment by ID from a Jira issue with optional expansions.
Get ComponentTool to retrieve components from Jira projects with search and filtering.
Get Create Field Metadata for Issue TypeTool to retrieve field metadata for a specific issue type in a project.
Get Current UserRetrieves detailed information about the currently authenticated Jira user.
Get DashboardsTool to list and search Jira dashboards visible to the current user.
Get Favorite FiltersTool to retrieve favorite filters for the current user.
Get fieldsTool to retrieve Jira issue fields metadata.
Get custom fields paginatedTool to retrieve Jira fields in pages.
Get FilterRetrieves a specific Jira saved filter by ID, including its JQL and sharing metadata, to reuse in subsequent searches.
Get GroupRetrieves details of a specific Jira group by name or ID.
Get Service Management InfoRetrieves runtime information for the Jira Service Management instance.
Get IssueRetrieves a Jira issue by ID or key with customizable fields and expansions.
Get Create Issue MetadataTool to retrieve issue creation metadata for Jira projects.
Get Issue Edit MetaTool to retrieve editable fields for a Jira issue.
Get Issue Link TypesRetrieves all configured issue link types from Jira.
Get issue pickerTool to get issue picker suggestions from Jira.
Get Issue PropertyRetrieves a custom property from a Jira issue by key.
Get Issue ResolutionsRetrieves all available issue resolution types from Jira.
Get issue typesRetrieves all Jira issue types available to the user using the modern API v3 endpoint; results vary based on 'Administer Jira' global or 'Browse projects' project permissions.
Get Issue WatchersRetrieves users watching a Jira issue for update notifications.
Get JQL autocomplete reference dataTool to retrieve JQL autocomplete reference data.
Get JQL autocomplete suggestionsTool to get JQL field auto-complete suggestions.
Get My PermissionsTool to retrieve the user's permissions in Jira.
Get User Locale PreferenceTool to retrieve the locale preference of the currently authenticated Jira user.
Get PermissionsTool to retrieve all available Jira permissions.
Get Permitted ProjectsTool to retrieve projects where the current user has specific permissions.
Get ProjectRetrieves details of a Jira project by its ID or key.
Get Project RolesRetrieves all available roles for a Jira project.
Get Project TypeRetrieves detailed information about a specific Jira project type by its key.
Get Project VersionsRetrieves all versions for a Jira project with optional expansion.
Get Recent ProjectsRetrieves a list of projects recently accessed by the authenticated user.
Get Issue Remote LinksRetrieves links from a Jira issue to external resources.
Get Server InfoTool to retrieve Jira instance server information.
Get Service Desk Request Type FieldsTool to retrieve JSM request type field metadata for filling out portal requests.
Get System AvatarsTool to retrieve all system avatars for a specific type (issuetype, project, user, or priority).
Get TransitionsRetrieves available workflow transitions for a Jira issue.
Get Universal Avatar Type OwnerTool to retrieve all avatars (system and custom) for a specific type and entity in Jira.
Get Universal Avatar View TypeTool to retrieve the default avatar image for a specific type (project, issuetype, or priority) from Jira.
Get Avatar ImageTool to retrieve a specific avatar image by type and ID from Jira.
Get Issue VotesFetches voting details for a Jira issue; requires voting to be enabled in Jira's general settings.
Get WorklogsRetrieves worklogs for a specified Jira issue.
List All ProjectsTool to list all projects accessible to the user.
List BoardsRetrieves paginated Jira boards with filtering and sorting options.
List Comments by IDsTool to retrieve multiple comments by their IDs in a single request.
List Jira FiltersTool to search and list Jira saved filters (saved searches) visible to the current user.
List Groups (Picker)Tool to search and list groups using Jira's picker endpoint.
List Issue CommentsRetrieves paginated comments from a Jira issue with optional ordering.
List Project TypesRetrieves all Jira project types available in the instance.
List SprintsRetrieves paginated sprints from a Jira board with optional state filtering.
Move Issues to SprintMoves one or more Jira issues to a specified active sprint.
Parse JQL QueriesParse and validate JQL queries, returning their abstract syntax tree structure along with any errors or warnings.
Remove User from GroupRemoves a user from a Jira group.
Remove User from Project RoleRemoves a user or group from a project role.
Remove Watcher from IssueRemoves a user from an issue's watcher list by account ID.
Search Approximate CountCount issues matching a JQL query using approximate count endpoint.
Search DashboardsTool to search for Jira dashboards with filtering, sorting, and pagination support.
Search Issues Using JQL (GET)Searches for Jira issues using JQL with pagination and field selection.
Search issuesAdvanced Jira issue search supporting structured filters and raw JQL.
Send Notification for IssueSends a customized email notification for a Jira issue.
Transition IssueTransitions a Jira issue to a different workflow state, with support for transition name lookup and user assignment by email.
Update CommentUpdates text content or visibility of an existing Jira comment.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Jira connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Jira via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Jira MCP URL

Create a Composio Tool Router session for Jira

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["jira"])

url = session.mcp.url
What's happening:
  • You create a Jira only session through Composio
  • Composio returns an MCP HTTP URL that exposes Jira tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Jira and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["jira"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Jira through Composio's Tool Router. The agent can perform Jira operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

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FAQ

What are the differences in Tool Router MCP and Jira MCP?

With a standalone Jira MCP server, the agents and LLMs can only access a fixed set of Jira tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Jira and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Jira tools.

Can I manage the permissions and scopes for Jira while using Tool Router?

Yes, absolutely. You can configure which Jira scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Jira data and credentials are handled as safely as possible.

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