How to integrate Jira MCP with LlamaIndex

This guide walks you through connecting Jira to LlamaIndex 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 LlamaIndex 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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Introduction

This guide will help you understand how to give your LlamaIndex 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

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI CrewAI

TL;DR

Here's what you'll learn:

Set your OpenAI and Composio API keys
Install LlamaIndex and Composio packages
Create a Composio Tool Router session for Jira
Connect LlamaIndex to the Jira MCP server
Build a Jira-powered agent using LlamaIndex
Interact with Jira through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

ReAct Agent: Reasoning and acting pattern for tool-using agents
MCP Tools: Native support for Model Context Protocol
Context Management: Maintain conversation context across interactions
Async Support: Built for async/await patterns

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:

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

Step-by-step Guide

Step by step10 STEPS

Prerequisites

Before you begin, make sure you have:

Python 3.8/Node 16 or higher installed
A Composio account with the API key
An OpenAI API key
A Jira account and project
Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Jira

OpenAI API key (OPENAI_API_KEY)

Go to the OpenAI dashboard
Create an API key if you don't have one
Assign it to OPENAI_API_KEY in .env

Composio API key and user ID

Log into the Composio dashboard
Copy your API key from Settings
- Use this as COMPOSIO_API_KEY
Pick a stable user identifier (email or ID)
- Use this as COMPOSIO_USER_ID

Installing dependencies

npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv

Create a new Typescript project and install the necessary dependencies:

@composio/llamaindex: Composio's LlamaIndex integration
@llamaindex/openai: OpenAI LLM integration
@llamaindex/tools: MCP client for LlamaIndex
@llamaindex/workflow: Workflow framework for LlamaIndex
dotenv: Environment variable management

Set environment variables

bash

OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

Authenticate with OpenAI's GPT-5 model
Connect to Composio's Tool Router
Identify your Composio user session for Jira access

Import modules

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

Create a new file called jira_llamaindex_agent.ts and import the required modules:

Key imports:

dotenv.config loads .env at runtime
readline gives us a simple CLI chat loop
Composio is the main Composio SDK client
mcp connects to an MCP endpoint
createAgent builds a LlamaIndex agent
openai configures the LLM backend

Load environment variables and initialize Composio

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["jira"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Jira actions." ,
    llm,
    tools,
  });

  return agent;
}

What's happening here:

We create a Composio client using your API key and configure it with the LlamaIndex provider
We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, jira)
The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
LlamaIndex will connect to this endpoint to dynamically discover and use the available Jira tools.
The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

What's happening:

We're creating a direct terminal interface to chat with Jira
The LLM's responses are streamed to the CLI for faster interaction.
The agent uses context to maintain conversation history
The agent processes the request, selects appropriate Jira tools, and returns a result
We extract the answer from the result data structure and display it to the user
You can type 'quit' or 'exit' to stop the chat loop gracefully
Agent responses and any errors are streamed in a clear, readable format

Define the main entry point

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();

What's happening here:

We're orchestrating the entire application flow
The agent gets built with proper error handling
Then we kick off the interactive chat loop so you can start talking to Jira

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Jira, then start asking questions.

Complete Code

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

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["jira"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Jira actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();

Conclusion

You've successfully connected Jira to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:

Tool Router dynamically exposes Jira tools through an MCP endpoint
LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
The agent becomes more capable without increasing prompt size
Async Python provides clean, efficient execution of agent workflows

You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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

Use Jira MCP with ChatGPT

OpenAI Agents SDK

Use Jira MCP with OpenAI Agents SDK

Claude Agent SDK

Use Jira MCP with Claude Agent SDK

Claude Code

Use Jira MCP with Claude Code

Claude Cowork

Use Jira MCP with Claude Cowork

Codex

Use Jira MCP with Codex

Cursor

Use Jira MCP with Cursor

OpenClaw

Use Jira MCP with OpenClaw

Hermes

Use Jira MCP with Hermes

CLI

Use Jira MCP with CLI

Google ADK

Use Jira MCP with Google ADK

LangChain

Use Jira MCP with LangChain

Vercel AI SDK

Use Jira MCP with Vercel AI SDK

Mastra AI

Use Jira MCP with Mastra AI

CrewAI

Use Jira MCP with CrewAI

OpenCode

Use Jira MCP with OpenCode

VS Code

Use Jira MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Google Sheets

Oauth2

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Notion

Oauth2Api Key

Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

Airtable

Oauth2Api Key

Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.

Asana

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Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.

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. LlamaIndex 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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