Claude Atlassian Connector: Connect Claude to Jira & Confluence Securely

Connecting Claude to Atlassian gives it the same reach as the person who authorized it. You can use it to find an issue, summarize a project, search documentation, update a Jira issue, or add a comment.

While this can take a lot of manual work off your plate, it raises security concerns. It is difficult to tell what exactly Claude sees and what all things it can do when it is connected to your Jira or Confluence instance.

Atlassian's Rovo MCP server uses OAuth 2.1 by default and respects the authorizing user's existing Atlassian permissions. Atlassian also provides organization-level controls for MCP connections, including controls for read, write, and search permissions, along with domain and authentication settings.

This is useful. But what if you have more specific AI governance requirements?

You may want developers to use Claude with engineering projects while keeping HR, finance, and security projects out of reach. You may want Claude to search Jira but not create or update anything. You may want to block destructive actions entirely.

With miniOrange AI Agent Governance for Jira & Confluence (Claude & ChatGPT), you connect Claude or ChatGPT through MCP and place a policy layer between the AI assistant and your Atlassian data. You can control access by user group, Jira project, Confluence space, and operation, and then audit every AI call from a centralized interface.

What Is the Claude Atlassian Connector?

A Claude Atlassian connector lets Claude work with Atlassian products through a connected interface. With MCP, or Model Context Protocol, Claude can use supported tools to access information and perform actions in connected systems.

For Jira and Confluence, this can include searching and reading information, creating or updating content, and adding comments. Atlassian's own Rovo connector for Claude currently supports read and write capabilities across Jira, Confluence, and other Atlassian products.

However, the AI assistant should not have every capability available to the person who authorized the connection.

miniOrange adds a governance layer in front of that connection and evaluates AI requests against your policies. Each request is checked before it reaches Jira or Confluence, and each call is captured for audit.

A Direct Claude-to-Jira Connection Inherits Everything the User Can Reach

When you connect Claude to Jira or Confluence through the native Rovo MCP flow, the AI acts on behalf of the user who authorizes it. Its access is therefore subject to that user's existing Atlassian permissions, which can be risky.

Let’s say a developer has access to 100 Jira projects. Once Claude is authorized to act through that user's Atlassian access, it can potentially reach the projects that fall within both the user's permissions and the organization's MCP controls.

It can also make governance harder once you have a large Jira or Confluence environment.

What if you want Claude to work with only 10 of those projects?

Atlassian provides organization-level controls for MCP access, including separate controls for read, write, and search permissions, along with domain, authentication, and IP allowlist controls. But native controls do not provide the same granular, agent-specific policy controls for user groups, projects, spaces, and individual operations.

Read access is not your only concern. The same Claude Jira connector that summarizes an issue can also create, update, comment on, and delete data.

Without granular controls, risks like prompt injection could trick an agent into executing unapproved actions. Atlassian's own guidance tells admins to apply least privilege, review high-impact changes, and monitor audit logs, but native settings lack a built-in way to enforce these limits on the agent.

Without a governance layer, Claude's access to Jira grows with every user who connects. Write and destructive actions remain available through the same connection, and visibility into AI activity can be fragmented across native logs.

Put a Governance Layer Between Claude and Your Atlassian Data

The safest approach gives AI agents a governed, task-scoped path into Jira data rather than broad API access. miniOrange extends this model.

Claude or ChatGPT connects to the miniOrange app through MCP instead of connecting directly to Atlassian. The app evaluates each AI request against your configured rules. The request is then allowed or blocked based on those rules. Every call is also captured for audit.

The workflow comes down to four moves.

• Scope: Decide which user groups, Jira projects, and Confluence spaces the AI workflow can reach.
• Control: Allow or block specific operations, including fetch, create, update, delete, and comment.
• Enforce: Check every AI request against your rules before it touches Atlassian data.
• Prove: Keep a searchable record of every AI call in the Activity Log.

Core Capabilities of miniOrange AI Agent Governance for Jira & Confluence

1. Control AI Access by User Group

With group-based policies, you can define access rules around Atlassian user groups. For example, you could allow a developers group to use Claude with selected engineering projects while keeping other project areas outside the AI workflow's reach.

In this approach, you are not changing the user’s permissions but the AI’s.

2. Restrict Jira Projects and Confluence Spaces

A broad Atlassian connection can be difficult to govern when your site contains hundreds of projects and spaces. AI does not need access to all of that. Maybe only a small subset.

miniOrange lets you scope rules to specific Jira projects and Confluence spaces. This allows you to keep the AI workflow focused on the data it actually needs. The user's own Atlassian access remains unchanged.

3. Control Operations, Not Just Data

A Claude Jira connector that can read an issue can be useful for summaries, triage, reporting, and analysis. But the risk increases when it can also execute write operations. It might be able to create an issue, update its fields, add a comment, or delete an item depending on the tools exposed through the connection.

With miniOrange, you can allow Claude to fetch issues while blocking create, update, delete, or comment actions wherever write access is inappropriate.

This gives you a practical way to separate read vs. write access for AI agents.

4. Enforce Policies Before AI Access

With miniOrange, each AI request is evaluated against your Access Policy before the AI reaches Jira or Confluence data. You define a default Allow or Deny decision and then add ordered rules. The first matching rule applies.

And because rules are evaluated on the next AI request after you save the policy, you do not have to redesign your users' underlying Jira or Confluence permissions to change the AI behavior.

5. Audit Every AI Action

Every AI action through the miniOrange app is captured in the Activity Log, whether it was allowed or blocked. You get details such as the user, AI source, operation, decision, and result.

You can also inspect an individual event for more context. The detail view shows:

• the user who triggered the request
• the user's Atlassian groups
• the exact arguments sent by the AI
• the decision made by policy
• the rule that applied when an action was blocked
• response size
• latency
• the corresponding Atlassian audit JSON

6. Built on Atlassian Forge

The miniOrange AI Agent Governance app is built on Atlassian Forge, so the governance layer runs within Atlassian's Forge environment rather than relying on an external application service.

How It Works

Setting up your Claude Atlassian connector with miniOrange is pretty straightforward.

Step 1: Install the App

Install AI Agent Governance for Jira & Confluence (Claude & ChatGPT) from the Atlassian Marketplace and open the app in your Atlassian environment.

Step 2: Connect Claude

Configure Claude to connect to the miniOrange MCP server instead of connecting directly to Atlassian. Each person signs in individually through Atlassian so the app can identify the user and their Atlassian groups.

This gives the governance layer the user context it needs to apply group-based policies and associate actions with a real user.

Step 3: Define Policies

Set a default Allow or Deny decision, then create rules based on:

• AI client
• user group
• operation
• Jira project or Confluence space
• effect

Step 4: Enforce

Every AI request is evaluated against your rules before the operation proceeds. Changes take effect on the very next AI call.

Step 5: Monitor

Review the Activity Log and governance dashboard to see what Claude or ChatGPT actually did. You get a continuous feedback loop between policy and activity.

Read the step-by-step setup guide to get a clear understanding of how to install the app.

Practical Use Cases for Governed Claude Access

1. Protect Sensitive Projects

You can define restrictions by groups or projects. For instance, let your engineering teams use Claude with selected Jira projects while keeping confidential HR, finance, and security projects outside the AI workflow.

2. Enforce Read-Only Mode

Allow Claude to fetch and search Jira issues, but block create, update, delete, and comment operations across your site.

3. Prevent Destructive Actions

You can create a policy that blocks delete operations globally so AI requests cannot delete Jira issues or Confluence pages through the governed connection.

4. Scope Confluence Access

You may want Claude to search engineering documentation but not restricted business or security content. Scope the policy to the Confluence spaces that the AI workflow needs. This gives you a more controlled way to connect Claude to Jira and Confluence securely.

5. Inspect AI Actions

When an AI action needs review, open the corresponding audit event and inspect the exact request, decision, user information, response details, and latency.

Governance & Compliance Standards

Why Teams Use miniOrange to Govern Claude & ChatGPT in Atlassian

Choosing miniOrange for your Claude Atlassian connector provides a dedicated control layer for enterprise AI adoption:

• Atlassian Marketplace Security: Built specifically for Atlassian admins, IT teams, and compliance officers.
• Independent Access Control: Govern what Claude and ChatGPT can do without modifying underlying user roles in Atlassian.
• Multi-Agent Support: Secure both Claude and ChatGPT through one centralized governance app.
• Operation-Level Control: Fine-tune permissions for fetch, create, update, delete, and comment tools.
• Pre-Access Enforcement: Block unauthorized operations before the agent accesses your data.
• Deep Audit Visibility: View request arguments, response size, latency, and policy decisions through the Activity Log and governance dashboard.
• 100% Forge-Native: Runs inside Atlassian, so no data leaves your environment.

FAQs

1. How do I connect Claude to Jira and Confluence?

You can connect Claude to Atlassian through MCP. With miniOrange AI Agent Governance for Jira & Confluence, Claude connects to the miniOrange MCP endpoint instead of connecting directly to Atlassian. Users sign in individually through Atlassian, after which the miniOrange app can apply group-based policies and govern AI requests.

2. Does Claude get the same permissions as the user who connects it?

Atlassian's native Rovo MCP access is scoped to the authorizing user's existing Atlassian permissions.

miniOrange adds a separate AI governance layer on top of those permissions. You can restrict the AI by user group, Jira project, Confluence space, and operation without changing the user's own Jira or Confluence permissions.

3. Can I give Claude read-only access to Jira?

Yes. You can configure policies that allow fetch and search operations while blocking create, update, delete, and comment actions.

This lets you build a read-oriented AI workflow instead of giving the AI unrestricted write capabilities.

4. Can I stop an AI agent from deleting Jira issues or Confluence pages?

Yes. You can deny delete operations through the Access Policy. A rule such as delete* can block delete-related AI actions across the governed connection.

5. How is this different from Atlassian's native MCP controls?

Atlassian provides native controls for managing Rovo MCP access, including read, write, and search permissions, authentication methods, trusted domains, and related organization-level controls.

miniOrange adds a separate AI governance layer focused on finer-grained policy decisions around user groups, Jira projects, Confluence spaces, and individual operations. It is designed to work alongside, not replace, your existing Atlassian security controls.

6. How do I see what Claude or ChatGPT actually did in Jira and Confluence?

Open the miniOrange Activity Log to review AI actions. You can see the user, AI source, operation, decision, and result, then open individual events for the exact arguments, response size, latency, policy decision, and other audit context.