> **Building with AI coding agents?** If you're using an AI coding agent, install the official Scalekit plugin. It gives your agent full awareness of the Scalekit API — reducing hallucinations and enabling faster, more accurate code generation.
>
> - **Claude Code**: `claude plugin marketplace add scalekit-inc/claude-code-authstack && claude plugin install <auth-type>@scalekit-auth-stack`
> - **GitHub Copilot CLI**: `copilot plugin marketplace add scalekit-inc/github-copilot-authstack` then `copilot plugin install <auth-type>@scalekit-auth-stack`
> - **Codex**: run the bash installer, restart, then open Plugin Directory and enable `<auth-type>`
> - **Skills CLI** (Windsurf, Cline, 40+ agents): `npx skills add scalekit-inc/skills --list` then `--skill <skill-name>`
>
> `<auth-type>` / `<skill-name>`: `agentkit`, `full-stack-auth`, `mcp-auth`, `modular-sso`, `modular-scim` — [Full setup guide](https://docs.scalekit.com/dev-kit/build-with-ai/)

---

# Atlassian Rovo MCP connector

1. ### Install the SDK

   ```bash frame="terminal"
       npm install @scalekit-sdk/node
       ```
     ```bash frame="terminal"
       pip install scalekit
       ```
     Full SDK reference: [Node.js](/agentkit/sdks/node/) | [Python](/agentkit/sdks/python/)

2. ### Set your credentials

   <AgentKitCredentials />

3. ### Set up the connector

   Register your Atlassian Rovo MCP credentials with Scalekit so it handles the token lifecycle. You do this once per environment.

   <details>
   <summary>Dashboard setup steps</summary>

   <SetupAtlassianmcpSection />

   </details>

4. ### Authorize and make your first call

   <QuickstartGenericOauthSection connector="atlassianmcp" toolName="atlassianmcp_fetch" providerName="Atlassian Rovo MCP" toolInputNode="{ id: 'https://example.com/id' }" toolInputPython='{"id":"https://example.com/id"}' />

## What you can do

Connect this agent connector to let your agent:

- **Manage Jira issues** — create, edit, transition, comment on, and link issues; add worklogs
- **Search with JQL** — query issues using Jira Query Language with full field and filter support
- **Work with Confluence** — create, update, and retrieve pages; add footer and inline comments
- **Manage Compass components** — create, get, and search services, libraries, and applications; define custom fields and relationships
- **Look up users and resources** — resolve Atlassian account IDs, list accessible cloud sites, and find project metadata
- **Fetch Atlassian content** — retrieve any Atlassian object by its ARI or URL (e.g. a Jira issue or Confluence page URL)

## Common workflows

<SectionAfterSetupAtlassianmcpCommonWorkflows />

## Tool list

Use the exact tool names from the **Tool list** below when you call `execute_tool`. If you're not sure which name to use, list the tools available for the current user first.

<ToolList tools={tools} />

---

## More Scalekit documentation

| Resource | What it contains | When to use it |
|----------|-----------------|----------------|
| [/llms.txt](/llms.txt) | Structured index with routing hints per product area | Start here — find which documentation set covers your topic before loading full content |
| [/llms-full.txt](/llms-full.txt) | Complete documentation for all Scalekit products in one file | Use when you need exhaustive context across multiple products or when the topic spans several areas |
| [sitemap-0.xml](https://docs.scalekit.com/sitemap-0.xml) | Full URL list of every documentation page | Use to discover specific page URLs you can fetch for targeted, page-level answers |