Atlassian Opens 150-Billion-Object Graph To Claude Code Agents

Atlassian dropped the wall around its 150-billion-object Teamwork Graph on Wednesday and invited Claude Code in. The Sydney-based software maker used its Team ’26 keynote in Anaheim to unveil Max, a “mini Claude Code” mode inside Rovo Chat, and put the same context substrate behind any MCP-compliant agent, per Atlassian’s Team ’26 founder update.

Max runs long, autonomous jobs against Atlassian’s map of Jira tickets, Confluence pages, Jira Service Management incidents, and connected SaaS data. The new Teamwork Graph CLI and a set of MCP servers, both in open beta, give outside agents like Anthropic’s Claude Code and OpenAI’s Codex the same relational queries Rovo uses internally. Pricing flips to consumption-based for Max usage.

The pitch from Atlassian’s head of product for AI, Jamil Valliani, is straightforward. Whatever else changes in agentic software, the agent that knows where your meeting notes live, who owns which incident, and which Jira ticket killed which sprint will win. Atlassian thinks that agent runs on its graph.

Internal benchmarks, the company says, back the bet. Claude Code with Teamwork Graph CLI access used 48 percent fewer tokens and produced 44 percent more accurate results than the same agent without it. Both numbers come from Atlassian’s own testing, not an outside lab.

Max Acts Like Claude Code, Built On Atlassian’s Memory

Max is the brand for the long-running autonomous mode inside Rovo Chat. Valliani calls it a “mini Claude Code” running in the cloud with full Teamwork Graph context loaded by default. Where Rovo today answers a knowledge question, Max takes a multi-step task and works it through.

Think product manager work, not IDE work. Pull the last six quarters of customer escalations from Jira Service Management, cross-reference Confluence retros, draft a remediation plan, file the tickets. Max can run a job that takes minutes or 20 minutes, Valliani told The New Stack, with the agent reasoning over relationships rather than dumping raw documents into the prompt window.

The inside-Rovo placement matters because most knowledge workers will never open a terminal or write a graph query. Max meets them in chat. Atlassian says it has watched a sevenfold jump in agentic automations across its customer base over the past six months, a trajectory the company is using to justify the new mode’s existence.

The 150 Billion Connections Behind The Graph

The Teamwork Graph has been quiet infrastructure inside Atlassian for years. Valliani describes it as “system of record level quality,” meaning the kind of data fabric a company would let payroll or compliance run against. Years of Jira ticket history, Confluence page edits, JSM incident timelines, and external SaaS signals get mapped into people, projects, decisions, and documents with relationships drawn between them.

Customers will, for the first time, get to see what their own piece of the graph looks like. A new public site at teamworkgraph.com will visualize the graph for any logged-in customer. Visualization closes the loop for buyers who want to understand exactly what they’re paying for.

The numbers Atlassian is putting on the asset are large by any read.

• 150 billion objects and relationships across Jira, Confluence, and Jira Service Management plus connected SaaS tools.
• 48 percent fewer tokens used by Claude Code when querying the graph through the new CLI versus baseline retrieval.
• 44 percent higher accuracy on internal task completion benchmarks with graph access.
• Over 1 billion lines of code indexed for code intelligence searches inside Rovo.

Mike Cannon-Brookes, the co-founder and CEO who has run the company alongside Scott Farquhar since 2002, framed the asset bluntly in the press briefing. The graph is what every customer already has on Atlassian’s cloud. The new tooling just lets them aim it.

That framing matters because the company reported $1.43 billion in revenue for its fiscal third quarter ending in March 2026, with cloud revenue growth still its loudest number. Selling AI tools that pull from data customers already host with Atlassian is a defensible motion. Selling AI tools that require customers to migrate data is not.

Why Multi-Hop Reasoning Beats A Stuffed Context Window

The technical pitch over standard retrieval-augmented generation is direct. A RAG agent dumps document chunks into the model’s context window and hopes the right ones make it in. A graph-aware agent traverses relationships, asking the data fabric who owns a ticket, what decisions touched it, and which incidents share the same root cause. “The context window is not stuffed anymore,” Valliani says. “You can actually use reasoning power where it belongs, not just to sit through a bunch of data.”

Atlassian exposes the graph through Cypher, the open graph query language Neo4j authored, paired with GraphQL for relational queries, per the platform’s Atlassian Teamwork Graph Cypher and GraphQL documentation. Multi-hop traversal lets an agent ask one question that resolves to dozens of joins, returning a curated set of nodes instead of a haystack of paragraphs.

Atlassian Hands Outside Agents A Key To Its Own Vault

The headline product for developers is the new Teamwork Graph CLI, in open beta as of this week. It gives any coding agent a terminal interface to the same context Rovo enjoys internally. Atlassian’s own Teamwork Graph CLI and Rovo MCP decision guide sketches how teams should pick between the CLI and the MCP servers depending on whether they want to drive agents from the terminal or from inside an existing client.

For a developer running Claude Code in an IDE, the practical change is the absence of glue code. Asking the agent which Jira tickets and Confluence decisions touched a file used to require a custom integration. Now the agent can call MCP tools and get back the relational context Rovo would have surfaced anyway.

Cannon-Brookes thinks the CLI is the sleeper hit of the show.

“The Teamwork Graph CLI is probably going to be the number one thing, I suspect, received by customers in terms of, it’s free, which always helps them, and it just unlocks the existing graph they have in all these new ways,” Cannon-Brookes said in a press briefing ahead of the keynote.

Concrete things customers can run through the CLI:

• Ask Claude Code or Codex which repositories haven’t yet adopted a new design system component, scoped across Atlassian’s billion-line code intelligence index.
• Pull the chain of decisions, owners, and Confluence pages tied to a specific Jira epic before drafting a status report.
• Run incident triage by cross-referencing JSM tickets against connected SaaS observability data without an additional ETL pipeline.
• Hand a coding agent a sprint and have it generate the dependency graph, file the missing tickets, and assign owners by name.

“We’ve been an open platform company from day one, so we’ve never wanted to constrain somebody to use only one thing,” Valliani says. The trade is access for stickiness. If the graph is genuinely the differentiator, letting Claude Code query it makes Atlassian more sticky, not less.

Variable Jobs Demand Variable Bills

Today’s Rovo entitles actions per seat, with a credit pool baked into each Atlassian plan. Overage charges have not yet been switched on. Max is moving to a different model. Atlassian plans to bill Max usage on a variable, value-based basis, with rate cards and overage timing to be published “relatively soon,” according to Valliani.

The reasoning is mechanical. A five-minute Max job and a 20-minute Max job cannot reasonably cost the same amount, especially when both are dispatched from the same chat thread. Per-seat math breaks the moment one user fires off the equivalent of a half-hour pipeline run.

Cannon-Brookes prefers the hybrid model the company already runs. The seat covers a generous Rovo credit allowance, generous index storage, and Forge limits that should cover what he calls “the vast majority of customers.” The user who pushes millions of objects into the graph is the user willing to pay overage. Monday.com’s recast of itself as an AI work platform earlier this week leaned on the same logic, with native agents priced against credits rather than flat seats.

Every Big Vendor Wants The Same Moat Now

The bet Atlassian is making is not unique. Microsoft pitches Microsoft Graph plus Copilot Studio. Salesforce pitches Data Cloud plus Agentforce, recently extended through an April 2026 partnership with Google Cloud that lets agents act across both vendors’ platforms. ServiceNow rolled out a stack of agent tools at its own Knowledge 2026 event the same week as Team ’26. Google launched Agentic Data Cloud at Cloud Next 2026, anchored by its Knowledge Catalog.

The Gartner read is that the underlying battlefield has moved. Adam Ronthal, VP analyst at Gartner, called context the new critical infrastructure in the firm’s March 2026 keynote on data and analytics, per Gartner’s 2026 data and analytics predictions release. “Context graphs track not only data context but also decision flows and event traces, enabling more informed and effective business decision making by AI agents,” Ronthal said.

How each vendor packages the pitch:

Moor Insights and Strategy’s analyst insight on Google’s context redefinition argued that the platform owning the trusted context layer wins the agent question by default, because the model can be swapped while the graph cannot. Atlassian agrees with the conclusion. The route differs.

Glean, the enterprise search vendor that doubled annual recurring revenue to $200 million in 2025, has been making the same context-graph argument for two years. Investor appetite for AI infrastructure has shifted accordingly. The substrate underneath the agent now sells better than the agent itself.

Frequently Asked Questions

How Do I Try The Teamwork Graph CLI Today?

It’s open beta as of May 6, 2026, and free for any Atlassian Cloud customer. Sign in with admin credentials, install the CLI from Atlassian’s developer portal, and authenticate against your tenant. The CLI exposes Cypher and GraphQL queries against the same Teamwork Graph that Rovo uses. Org admins can also visualize the graph at teamworkgraph.com without writing a single query.

Will Max Cost Extra On Top Of My Rovo Plan?

Yes. Max moves to variable, value-based pricing. Existing Rovo actions stay inside the per-seat credit pool, but Max jobs that run for minutes at a time will bill against a separate rate card. Atlassian has not published the rates yet. Valliani says they land “relatively soon.” Plan for overage line items if your team uses Max for long autonomous workflows on a regular basis.

Can My Claude Code Or Codex Agent Query Confluence Directly?

Yes, via the new MCP servers in open beta. Any MCP-compliant agent, including Anthropic Claude Code and OpenAI Codex, can call Teamwork Graph tools to retrieve Confluence pages, Jira tickets, and JSM incidents with their relationships intact. Permissions follow the user, so the agent only sees what the authenticated user can already see in the underlying products.

What Data Sits In The Graph By Default?

Jira tickets, Confluence pages, JSM incidents, Atlassian goals, teams, and users load automatically for any Atlassian Cloud customer. Connected SaaS tools like GitHub, Figma, and Slack feed the graph through Atlassian Connect or Forge integrations the admin opts into. No third-party data is added without an explicit connector being installed at the org level by an administrator.

Atlassian’s gamble is that the graph stays sticky even with third parties querying it. The harder question is whether customers see Max as worth a metered bill while Rovo stays in the per-seat envelope. Pricing transparency lands “relatively soon,” Valliani says, which is the answer companies give when the rate card is still being argued internally.

For now, the Teamwork Graph CLI ships free, the MCP servers ship in open beta, and Claude Code can finally see what Rovo always saw. The wall is down. The bill comes later.