How to integrate Jira MCP with LangChain

This guide walks you through connecting Jira to LangChain 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 LangChain 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 LangChain 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 LangChain 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

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Jira project to Composio
  • Create a Tool Router MCP session for Jira
  • Initialize an MCP client and retrieve Jira tools
  • Build a LangChain agent that can interact with Jira
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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 your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Jira functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Jira tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['jira']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Jira tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Jira tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "jira-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Jira MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Jira tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Jira related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['jira']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "jira-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Jira related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Jira through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
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

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

CrewAI logo

CrewAI

Use Jira MCP with CrewAI

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. LangChain 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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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.

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Abhi Arya
Co-founder, Opennote

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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.

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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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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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