Tool

Integrate with Jira to Fetch and Search Issues

Fetch Jira issues, comments, and projects, and run searches, from a LlamaIndex agent.

Works with jira

74
Spark score
out of 100
Updated 2 days ago
Version 0.14.23
Models
gpt 4ogpt 4

Add to Favorites

Why it matters

Connect your AI agent to Jira to seamlessly retrieve issue details, comments, and project information, and perform targeted issue searches.

Outcomes

What it gets done

01

Fetch specific Jira issues by key

02

Search for Jira issues containing keywords

03

List all Jira projects

04

Retrieve comments for a specific Jira issue

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/li-tool-tools-jira | bash

Overview

Jira Integration

A LlamaIndex tool that lets an agent fetch Jira issue details, search issues, list projects, and retrieve comments. Use for conversational lookup and search of Jira data, not for creating or modifying issues.

What it does

The Jira Integration tool lets a LlamaIndex agent fetch Jira issue details, comments, and projects, and perform searches against a Jira instance. The JiraToolSpec is initialized with a Jira server_url, an email, and an api_token, and once attached to an agent's tool list, the agent can answer natural-language requests about Jira data directly.

The source's own examples show the agent fetching a specific issue by its key ("Fetch Jira issue with the key 'PROJ-5' and give me the details"), searching for issues containing a keyword ("Search for Jira issues containing 'login bug'"), listing all Jira projects, and fetching all comments for a specific issue - covering issue lookup, keyword search, project listing, and comment retrieval as the four core capabilities exposed to the agent.

When to use - and when NOT to

Use it when you want a LlamaIndex agent to answer questions about Jira data conversationally - looking up a specific issue, searching by keyword, listing projects, or pulling comments - without the developer writing separate Jira API calls for each request type. Do not use it for creating or modifying Jira issues; the tool as documented covers fetching and searching, not write operations like creating tickets or posting comments.

Capabilities

Fetch a specific issue by key with full details, search for issues matching a keyword, list all Jira projects, and fetch all comments for a given issue - each triggered by a natural-language request to the agent.

How to install

from llama_index.tools.jira import JiraToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

tool_spec = JiraToolSpec(server_url=SERVER, email=EMAIL, api_token=API_KEY)

agent = FunctionAgent(
    tools=tool_spec.to_tool_list(),
    llm=OpenAI(model="gpt-4.1"),
)

Requires a Jira server URL, an account email, and an API token.

Who it's for

Developers building LlamaIndex agents that need to answer questions about Jira issues, comments, and projects conversationally, without hand-writing Jira API integration code.

Source README

Jira Integration

This tool integrates with Jira and enables fetching Jira issue details, comments, projects, and performing searches. You can query issues, retrieve specific issue details, or search for issues matching a keyword.

Usage

Here is the example usage:

from llama_index.tools.jira import JiraToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

tool_spec = JiraToolSpec(server_url=SERVER, email=EMAIL, api_token=API_KEY)

agent = FunctionAgent(
    tools=tool_spec.to_tool_list(),
    llm=OpenAI(model="gpt-4.1"),
)

### Fetch a specific Jira issue by key
response = await agent.run(
    "Fetch Jira issue with the key 'PROJ-5' and give me the details."
)
print(response)

### Search for issues containing a specific keyword
response = await agent.run("Search for Jira issues containing 'login bug'.")
print(response)

### Fetch all Jira projects
response = await agent.run("List all Jira projects.")
print(response)

### Fetch all comments for a specific issue
response = await agent.run("Fetch comments for Jira issue 'PROJ-5'.")
print(response)

FAQ

Common questions

Discussion

Questions & comments · 0

Sign In Sign in to leave a comment.