How to integrate Jira MCP with CrewAI

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.

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Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.

94 Tools3 Triggers

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

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

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.

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

Step by step08 STEPS
1

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
2

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.
3

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
4

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
5

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
6

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
7

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.
8

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
TOOLS & TRIGGERS

Supported Tools and Triggers

Every Jira action and event your agent gets out of the box.

Add Attachment

Uploads and attaches a file to a Jira issue.

Add Comment

Adds a comment using Atlassian Document Format (ADF) for rich text to an existing Jira issue.

Add Users to Project Role

Adds users and optionally groups to a project role.

Add User to Group

Adds a user to a Jira group.

Add Watcher to Issue

Adds a user to an issue's watcher list by account ID.

Add Worklog

Tool to add a worklog entry to a Jira issue.

Analyse Jira Expression

Analyses Jira expressions for syntax validation, type checking, and complexity analysis.

Assign Issue

Assigns a Jira issue to a user, default assignee, or unassigns; supports email/name lookup.

Bulk Create Issues

Creates multiple Jira issues (up to 50 per call) with full feature support including markdown, assignee resolution, and priority handling.

Check User Permissions

Check user permissions for global and project-level operations in Jira.

Create Group

Creates a new group in Jira with the specified name.

Create Issue

Creates a new Jira issue (e.

Link Issues

Links two Jira issues using a specified link type with optional comment.

Get JQL Autocomplete Data

Retrieves JQL autocomplete reference data including reserved words, field names, and function names.

Create Project

Creates a new Jira project with required lead, template, and type configuration.

Create Sprint

Creates a new sprint on a Jira board with optional start/end dates and goal.

Create Version

Creates a new version for releases or milestones in a Jira project.

Delete Comment

Deletes 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 Issue

Permanently and irreversibly deletes a Jira issue by its ID or key.

Delete Version

Deletes a Jira version and optionally reassigns its issues.

Delete Worklog

Deletes a worklog from a Jira issue with estimate adjustment options.

Edit Issue

Updates an existing Jira issue with field values and operations.

Evaluate Jira Expression

Tool to evaluate Jira expressions using the enhanced search API.

Bulk Fetch Issues

Tool to bulk fetch multiple Jira issues by their IDs or keys (max 100 per call).

Find Users 2

Tool to find users in Jira by query string, account ID, or property search.

Find Users For Picker

Find users for picker components by matching query against user attributes like display name and email.

Get All Groups

Retrieves all groups from the Jira instance with pagination support.

Get All Issue Type Schemes

Retrieves all Jira issue type schemes with optional filtering and pagination.

Get all projects

Retrieves all visible projects using the modern paginated Jira API with server-side filtering and pagination support.

Get Issue Statuses

Retrieves all issue statuses associated with workflows from Jira.

Get All Users

Retrieves all users from the Jira instance including active, inactive, app accounts, and system accounts, with pagination support.

Get Attachment

Retrieves the binary content of a Jira attachment by ID.

Get Attachment Meta

Tool to retrieve Jira attachment settings including upload limits and enabled status.

Get Comment

Retrieves a specific comment by ID from a Jira issue with optional expansions.

Get Component

Tool to retrieve components from Jira projects with search and filtering.

Get Create Field Metadata for Issue Type

Tool to retrieve field metadata for a specific issue type in a project.

Get Current User

Retrieves detailed information about the currently authenticated Jira user.

Get Dashboards

Tool to list and search Jira dashboards visible to the current user.

Get Favorite Filters

Tool to retrieve favorite filters for the current user.

Get fields

Tool to retrieve Jira issue fields metadata.

Get custom fields paginated

Tool to retrieve Jira fields in pages.

Get Filter

Retrieves a specific Jira saved filter by ID, including its JQL and sharing metadata, to reuse in subsequent searches.

Get Group

Retrieves details of a specific Jira group by name or ID.

Get Service Management Info

Retrieves runtime information for the Jira Service Management instance.

Get Issue

Retrieves a Jira issue by ID or key with customizable fields and expansions.

Get Create Issue Metadata

Tool to retrieve issue creation metadata for Jira projects.

Get Issue Edit Meta

Tool to retrieve editable fields for a Jira issue.

Get Issue Link Types

Retrieves all configured issue link types from Jira.

Get issue picker

Tool to get issue picker suggestions from Jira.

Get Issue Property

Retrieves a custom property from a Jira issue by key.

Get Issue Resolutions

Retrieves all available issue resolution types from Jira.

Get issue types

Retrieves 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 Watchers

Retrieves users watching a Jira issue for update notifications.

Get JQL autocomplete reference data

Tool to retrieve JQL autocomplete reference data.

Get JQL autocomplete suggestions

Tool to get JQL field auto-complete suggestions.

Get My Permissions

Tool to retrieve the user's permissions in Jira.

Get User Locale Preference

Tool to retrieve the locale preference of the currently authenticated Jira user.

Get Permissions

Tool to retrieve all available Jira permissions.

Get Permitted Projects

Tool to retrieve projects where the current user has specific permissions.

Get Project

Retrieves details of a Jira project by its ID or key.

Get Project Roles

Retrieves all available roles for a Jira project.

Get Project Type

Retrieves detailed information about a specific Jira project type by its key.

Get Project Versions

Retrieves all versions for a Jira project with optional expansion.

Get Recent Projects

Retrieves a list of projects recently accessed by the authenticated user.

Get Issue Remote Links

Retrieves links from a Jira issue to external resources.

Get Server Info

Tool to retrieve Jira instance server information.

Get Service Desk Request Type Fields

Tool to retrieve JSM request type field metadata for filling out portal requests.

Get System Avatars

Tool to retrieve all system avatars for a specific type (issuetype, project, user, or priority).

Get Transitions

Retrieves available workflow transitions for a Jira issue.

Get Universal Avatar Type Owner

Tool to retrieve all avatars (system and custom) for a specific type and entity in Jira.

Get Universal Avatar View Type

Tool to retrieve the default avatar image for a specific type (project, issuetype, or priority) from Jira.

Get Avatar Image

Tool to retrieve a specific avatar image by type and ID from Jira.

Get Issue Votes

Fetches voting details for a Jira issue; requires voting to be enabled in Jira's general settings.

Get Worklogs

Retrieves worklogs for a specified Jira issue.

List All Projects

Tool to list all projects accessible to the user.

List Boards

Retrieves paginated Jira boards with filtering and sorting options.

List Comments by IDs

Tool to retrieve multiple comments by their IDs in a single request.

List Jira Filters

Tool 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 Comments

Retrieves paginated comments from a Jira issue with optional ordering.

List Project Types

Retrieves all Jira project types available in the instance.

List Sprints

Retrieves paginated sprints from a Jira board with optional state filtering.

Move Issues to Sprint

Moves one or more Jira issues to a specified active sprint.

Parse JQL Queries

Parse and validate JQL queries, returning their abstract syntax tree structure along with any errors or warnings.

Remove User from Group

Removes a user from a Jira group.

Remove User from Project Role

Removes a user or group from a project role.

Remove Watcher from Issue

Removes a user from an issue's watcher list by account ID.

Search Approximate Count

Count issues matching a JQL query using approximate count endpoint.

Search Dashboards

Tool 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 issues

Advanced Jira issue search supporting structured filters and raw JQL.

Send Notification for Issue

Sends a customized email notification for a Jira issue.

Transition Issue

Transitions a Jira issue to a different workflow state, with support for transition name lookup and user assignment by email.

Update Comment

Updates text content or visibility of an existing Jira comment.

FRAMEWORKS

How to build Jira MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Jira MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Jira MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Jira MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Jira MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Jira MCP with Claude Cowork

Codex logo

Codex

Use Jira MCP with Codex

Cursor logo

Cursor

Use Jira MCP with Cursor

OpenClaw logo

OpenClaw

Use Jira MCP with OpenClaw

Hermes logo

Hermes

Use Jira MCP with Hermes

CLI logo

CLI

Use Jira MCP with CLI

Google ADK logo

Google ADK

Use Jira MCP with Google ADK

LangChain logo

LangChain

Use Jira MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Jira MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Jira MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Jira MCP with LlamaIndex

OpenCode logo

OpenCode

Use Jira MCP with OpenCode

VS Code logo

VS Code

Use Jira MCP with VS Code

FAQ

Frequently asked questions

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.

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.

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.

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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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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Jerome Leclanche
Co-Founder, Ingram Technologies