jira-mcpA Go-based MCP (Model Control Protocol) connector for Jira that enables AI assistants like Claude to interact with Atlassian Jira. This tool provides a seamless interface for AI models to perform comm

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Reviewed by Daniel Nikulshyn·Updated July 2026

Overview

Jira MCP is a Go-based Model Control Protocol (MCP) connector for Jira that enables AI assistants to interact with Atlassian Jira. It provides a seamless interface for AI models to perform common tasks such as issue management, search, sprint management, status and transition tracking, comments, worklogs, history and audit, issue relationships, and version management. The MCP server is designed to solve real problems arising in modern software development, with tools such as retrieving detailed information about an issue, creating new issues, modifying existing issues, listing issue types, searching for issues, and more. It is an opinionated MCP server built from years of real-world software development experience, crafted to meet the daily workflows of engineers and automation QC teams.

Key features

Issue Management: jira_get_issue, jira_create_issue, jira_create_child_issue, jira_update_issue, jira_list_issue_types
Search: jira_search_issue
Sprint Management: jira_list_sprints, jira_get_sprint, jira_get_active_sprint, jira_search_sprint_by_name
Status & Transitions: jira_list_statuses, jira_transition_issue
Comments: jira_add_comment, jira_get_comments
Worklogs: jira_add_worklog

Pricing

Model: Free
Category: MCP Servers
Rating: No reviews yet

Use cases

Automating Issue Tracking

Use Jira MCP to automate issue tracking and management, such as retrieving detailed information about specific issues, creating new issues, and updating existing ones.

Streamlining Sprint Management

Utilize Jira MCP to streamline sprint management, including listing active and future sprints, retrieving detailed sprint information, and transitioning issues through their workflows.

Pros & Cons

Pros

Sophisticated tools for actual development needs
Designed to solve real problems in modern software development
Seamless interface for AI models to interact with Jira

Cons

May require careful installation and configuration
Limited information on scalability and performance

Battle record

Across 1 battle in the Pantheon.

1st

2nd

3rd

Last battle

#2
MCP Servers Showdown — July 6, 2024
Jul 6, 2024 · #2 of 4

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Q&A

Does jira-mcp support large-scale deployments?

The documentation notes limited information on scalability and performance, so while it works well for typical engineering and QC teams, further testing may be needed for very large or highly concurrent Jira environments.

Asked by Hana Kobayashi · Nov 2, 2025

What are the main challenges in installing and configuring jira-mcp?

Because it is a custom Go-based MCP server, users must set up the Go runtime, compile the binary, and configure Jira API credentials and network settings to expose the MCP endpoint; careful attention to these steps is required for a smooth deployment.

Asked by Nadia Petrova · Sep 7, 2025

What Jira workflows can the tool automate?

The connector covers issue management (create, update, list types), search, sprint management (list, get active, search by name), status transitions, adding comments, worklogs, and handling issue relationships and version management.

Asked by Jana Krejčí · Aug 27, 2025

How does jira-mcp enable AI assistants like Claude to interact with Jira?

jira-mcp implements the Model Control Protocol (MCP) in Go, providing a set of RPC-style tools such as jira_get_issue, jira_create_issue, and jira_transition_issue that AI models can call to perform common Jira operations directly from their code.

Asked by Vincenzo Greco · Aug 9, 2025