Jira Cloud MCP. Find any issue detail or status via JQL.
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Jira Cloud MCP Server connects your AI client to the Jira Cloud API. It lets your agent read project details, search issues using JQL, list users, and track task statuses across your entire development portfolio.
Instead of jumping between tabs, your AI client can find, analyze, and report on any task or bug in Jira.
What your AI agents can do
Add comment
The comment appears in the issue activity timeline visible to all project members.
Add a comment to a Jira issue
Assign issue
Use list_users to discover account IDs. Pass an empty string to unassign.
Assign a Jira issue to a specific user
Create issue
Requires the project key and a summary. Optionally set issue type (defaults to Task), description, and priority. Use list_issue_types and list_priorities to discover valid values for issuetype and priority names.
Create a new Jira issue (task, bug, story, etc.)
Retrieves a complete record for one specific issue, including its status, comments, and custom fields.
Finds multiple issues across your Jira instance using complex search criteria defined by Jira Query Language.
Returns a list of all available projects, allowing your AI client to understand the organizational scope.
Lists all defined issue statuses (e.g., To Do, Done) and priorities (e.g., High, Low) for filtering and reporting.
Fetches a directory of all users in Jira, useful for assigning tasks or identifying owners.
Gathers details on a specific project, including its lead, issue types, and categories.
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Jira Cloud MCP Server: 10 Tools for Issue & Task Management
Use these 10 tools to read and process Jira data, finding specific issues, mapping statuses, and gathering project context for AI analysis.
019e9a8fadd comment
The comment appears in the issue activity timeline visible to all project members. Add a comment to a Jira issue
019e9a8fassign issue
Use list_users to discover account IDs. Pass an empty string to unassign. Assign a Jira issue to a specific user
019e9a8fcreate issue
Requires the project key and a summary. Optionally set issue type (defaults to Task), description, and priority. Use list_issue_types and list_priorities to discover valid values for issuetype and priority names. Create a new Jira issue (task, bug, story, etc.)
019d75bdget issue
Retrieves all details, comments, and custom fields for a specific Jira issue key.
019d75bdget myself
Gets the current user's identity and permissions within Jira.
019d75bdget project
Retrieves the lead, issue types, and categories for a specific Jira project key or ID.
019d75bdlist dashboards
Lists all high-level reporting dashboards available to the authenticated user.
019d75bdlist issue types
Provides a list of all issue types (like Bug, Epic, Story) available in the instance.
019d75bdlist priorities
Lists all defined issue priorities (e.g., High, Medium, Low) to help gauge task urgency.
019d75bdlist projects
Lists all project keys, names, and IDs across the entire Jira instance.
019e9a8flist sprints
Requires the board ID which can be found in the board URL. List sprints for a Jira agile board
019d75bdlist statuses
Lists all possible issue statuses (e.g., To Do, In Progress) for mapping project workflows.
019e9a8flist transitions
Use this to find transition IDs before using transition_issue. List available workflow transitions for an issue
019d75bdlist users
Lists all users in Jira by display name or account ID.
019d75bdsearch issues
Searches for multiple issues using powerful filtering criteria defined by Jira Query Language (JQL).
019e9a8ftransition issue
g., "To Do" → "In Progress" → "Done"). Requires a transition ID — use list_transitions to discover valid IDs for the current issue state. Move a Jira issue to a different workflow status
019e9a8fupdate issue
Provide only the fields you want to change as a JSON string. Update fields on an existing Jira issue
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Make Your AI Do More
Start with Jira Cloud, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
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- Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector
Jira Cloud MCP Server connects your AI client straight to the Jira Cloud API. Your agent can read project details, search for issues using JQL, list users, and track task statuses across your whole development portfolio. You won't have to jump between tabs; your AI client can find, analyze, and report on any task or bug in Jira.
How Jira Cloud MCP Works
- 1 Your AI client determines the necessary action—for example, finding all 'Bug' issues in the 'CORE' project.
- 2 It calls the appropriate tool, like
search_issues, passing the specific JQL query (project = CORE AND issuetype = Bug). - 3 The MCP Server executes the query against Jira and returns a structured JSON list of issue keys, summaries, and statuses to your AI client.
The bottom line is that your AI client uses these tools to read the data and write the report; it doesn't change anything in Jira.
Who Is Jira Cloud MCP For?
The Product Manager who needs to know the exact status of a feature before a roadmap meeting. The QA Engineer who has to manually check status transitions across multiple projects. The DevOps team member who needs to audit issue assignments across the entire codebase. This is for anyone whose job involves translating Jira data into actionable insight.
Uses search_issues and get_project to aggregate status reports on feature readiness across multiple development teams.
Runs get_issue on specific bug keys and uses list_statuses to verify the correct workflow path was followed.
Employs list_users and list_priorities to quickly identify who is blocked, who owns the issue, and what the current organizational urgency is.
What Changes When You Connect
- Find the exact details on a single item. Use
get_issueto pull everything on a key like 'PROJ-123', including comments, status, and custom fields. You don't have to click through the issue view. - Search complex criteria instantly. Instead of writing a JQL query in the browser, your agent calls
search_issueswith criteria like 'project = X AND status = Open', getting an instant list of relevant tasks. - Understand the scope of work. Call
list_projectsto see every project key in the organization, or uselist_issue_typesto confirm if the correct type (Bug vs. Epic) exists before searching. - Audit team structure. Use
list_usersto get a clean list of every user, allowing your agent to find all issues assigned to a specific person without needing their email address. - Map the workflow. Call
list_statusesandlist_prioritiesto get the valid state machine for a project, letting your agent know what status transitions are possible. - Get project context. Use
get_projectto understand the foundational setup of a team's project, like its lead or available issue types, before running a detailed search.
Real-World Use Cases
Auditing a Feature Launch
A PM needs to confirm all related tasks for 'Project Phoenix' are done. The agent calls list_projects to confirm the key, then uses search_issues with JQL: project = Phoenix AND status = Done. Finally, it calls get_project to verify the project lead. The PM gets a single, aggregated report.
Investigating a Bug Report
A QA engineer receives a vague bug report. The agent uses get_issue on the provided key to pull the full context, checking comments for reproduction steps, and uses list_issue_types to confirm it's actually classified as a 'Bug'. The agent then reports the full context immediately.
Identifying a Blocked Team Member
A Scrum Master needs to find out who is blocking a release. They use list_users to confirm team members and then use search_issues with JQL: status = Blocked AND assignee = currentUser. This immediately flags the person and the task.
Understanding Project Scope
A new team member needs to know how a specific project is set up. They ask the agent to list the project details. The agent calls get_project to retrieve the lead, issue types, and categories, giving the new hire a full overview without manual navigation.
The Tradeoffs
Trying to search everything at once
Just throwing a vague query like 'find stuff for the marketing team' and expecting a full answer. This fails because the agent doesn't know which project keys or user IDs to narrow the search to.
→
First, call list_projects to narrow the scope. Then, use search_issues with a specific JQL filter (e.g., project = Marketing AND assignee = [user_id]). This makes the search targeted and actionable.
Assuming the issue key is correct
The user assumes 'PROJ-123' exists and asks for its details, but the key is wrong or the project was archived. The agent returns a generic error, wasting time.
→
Before calling get_issue, run list_projects to confirm the project key is active. If that fails, use search_issues with a broader JQL to find similar keys or check status.
Filtering manually after the search
The agent uses search_issues and gets 50 results, then has to manually ask the user to filter them by 'High' priority. This is inefficient.
→
Include the priority directly in the search. Call search_issues using JQL: project = X AND priority = High. This filters the results right at the source.
When It Fits, When It Doesn't
Use this MCP Server if your goal is to read, audit, or synthesize data from Jira. You need to know the status, history, or owner of a task.
Don't use this if you need to change the data (e.g., transition a status or add a comment). For updates, you'd need a separate write-access server. Also, if you only need to check a single, simple status (like 'Is the project active?'), sometimes list_projects is enough, but if you need the details of the status, always use get_issue.
The core decision is: Do I need a list of possible options (list_users, list_statuses) first, or do I have the exact search criteria (search_issues)? Start by listing to confirm the boundaries, then search for the data.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Jira Cloud. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 17 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Jira data is scattered across dozens of tabs and screens.
Right now, checking the status of a complex feature requires jumping from the roadmap board to the project backlog, opening the issue, checking the comments for context, and then cross-referencing the assignee's current load. It's a minimum of four clicks and three different screens just to get a clear picture.
With this MCP server, your agent handles the context switch. You ask for the status, and the agent calls `get_issue` or `search_issues`. It returns a clean, structured data object with the status, assignee, and all relevant comments—all in one response.
Jira Cloud MCP Server: Manage Issue & Task Details
You stop writing repetitive JQL queries or manually compiling lists of project keys. The agent handles the syntax, whether you're listing all projects with `list_projects` or querying for specific task types using `list_issue_types`.
The process is streamlined to one API call. You state the goal—'Find all open bugs for the UI team'—and the agent executes the necessary `search_issues` call to deliver the answer.
Common Questions About Jira Cloud MCP
How do I use the `search_issues` tool in Jira Cloud MCP Server? +
You must provide a valid JQL query string. The tool uses Jira Query Language (JQL) to filter results, so a query like project = MYPROJ AND status = Open works best. This returns issue keys, summaries, and statuses.
What information does `get_issue` retrieve? +
get_issue pulls a complete record for a single issue. This includes not only the summary and status but also all historical comments, priority level, and custom fields.
Can I find out which projects are available using `list_projects`? +
Yes, list_projects returns a list of all project keys, names, and IDs that the current user has access to. This is useful for knowing the scope of your search.
Is `get_project` better than `list_projects`? +
list_projects gives you a master list of every project. get_project is used when you already know the project key and need to know its specific configuration, like its lead or available issue types.
How do I check permissions with `get_myself`? +
Calling get_myself returns the authenticated user's information and permissions, confirming what data the agent is allowed to read from your Jira instance.
How do I list all available issue types using `list_issue_types`? +
It lists every issue type configured in your Jira instance. This helps you know exactly what types are valid for searching or creating content, like 'Bug' or 'Story'.
What is the difference between `list_projects` and `get_project`? +
Use list_projects to get a master list of all project keys and names. Then, use get_project with a specific key or ID to get detailed scope information for one project.
How can I check the status of all issues in a project using `search_issues`? +
You write a JQL query targeting the project and status. For example, project = MYPROJ AND status = Open pulls all open items from that specific project.
How do I get Jira API credentials? +
You need your Jira instance domain (e.g., acme.atlassian.net), your account email, and an API Token. You can generate an API Token in your Atlassian Account Settings under Security > API Token.
What is JQL? +
JQL (Jira Query Language) is a powerful tool that allows you to search for issues in Jira using a structured query syntax.
Can I see private projects? +
Your AI agent will only be able to see projects and issues that your Atlassian account has permission to access.
Multi-server workflows that include Jira Cloud MCP
MCP Workflow to Sync Sprint Knowledge
Your sprint ended, 14 tickets are done, and the PM is asking 'so what shipped?' , because nobody updated the Confluence release page since February
MCP Workflow to Triage GitHub Bugs Into Jira
Your AI agent triages bugs across Jira and GitHub, then emails the right person with full context
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