Atlassian, MCP 표면을 220개 도구로 확장하고 OpenAI와 지출 약정 체결

Atlassian의 재구축된 MCP 서버는 이제 일일 1,500만 건의 호출을 처리하고 220개 이상의 도구를 노출하며, 새로운 지출 약정으로 GPT-6 Astra가 Rovo의 멀티 모델 구성에 추가되지만 플랫폼의 모델 비종속 입장은 유지됩니다.

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TL;DR — 세 문장

  • Atlassian's rebuilt MCP server handles more than 15 million calls per day and exposes 220-plus tools across Jira, Confluence, Bitbucket, Loom and Goals (S1).
  • A new "spend commitment" runs from Atlassian to OpenAI; Rovo remains multi-model and Astra is explicitly not the default (S1).
  • Governance features include OAuth 2.1 + PKCE, per-user permission enforcement, tiered read/write/destructive actions, DLP via Atlassian Guard and org-wide audit logs (S1).

출처: key_takeaways (실제 필드, 최대 3개 항목). 사실과 분석은 별도로 표시됩니다.

Atlassian, MCP 표면을 220개 도구로 확장하고 OpenAI와 지출 약정 체결Editorial cover for a component sourcing brief. Chip motif; headline "Atlassian, MCP 표면을 220개 도구로 확장하고 OpenAI와 지출 약정 체결". Reported key numbers: 220 -plus. 1 cited source. Static cover (no animation).Atlassian, MCP 표면을 220개 도구로 확장하고 OpenAI와지출 약정 체결REPORTED KEY NUMBERS220 -plus1 sourceXAIPART
Cover image generated from data already shown on this page: the category motif, the headline, and reported key numbers. No decorative illustration; no third-party image.

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부품을 소싱하시겠습니까? 요청 보내기 → RFQ

Reported by VentureBeat on . Summarized and analyzed by XAIPART Editorial.

What happened

Atlassian announced an expansion of its partnership with OpenAI, adding GPT-6 Astra and the GPT-5.6 series to its platform and Rovo AI, and connecting the Teamwork Graph to ChatGPT and Codex through a rebuilt Model Context Protocol server.S1 The arrangement includes a commercial commitment that an OpenAI representative described as "effectively a spend commitment" - Atlassian committing dollars to OpenAI models and technology, not the reverse.S1

Atlassian was explicit that GPT-6 Astra is not becoming Rovo's default model; Rovo routes requests dynamically across providers through an internal AI gateway that balances capability, speed and cost per task.S1 The company's own MCP announcement cites Anthropic's head of enterprise product, Scott White, calling Atlassian's MCP "one of the most-used enterprise MCP integrations on Claude," and Atlassian reports that its server's token-savings claims were measured on Claude models.S1

The rebuilt MCP server now handles more than 15 million calls per day, exposes 220-plus tools across Jira, Confluence, Bitbucket, Loom and Goals, and uses up to 25% fewer tokens on comparable Jira and Confluence work in internal testing.S1 Jira Service Management support is listed as coming soon.S1 Governance features include Atlassian-hosted endpoints secured with OAuth 2.1 and PKCE, per-user permission enforcement at query time, separated read, write and destructive risk tiers with confirmation gates on higher-risk steps, Data Loss Prevention via Atlassian Guard, domain and IP allowlists, per-scope controls and org-wide audit logging, including an option to disable writes entirely.S1

GPT-6 Astra pricing is listed at $10 per million input tokens and $50 per million output, with Rovo credit consumption scaling to the models and compute used per task.S1 OpenAI reports Astra reached the "Critical" cybersecurity threshold under its Preparedness Framework and scored 100% on one exploit benchmark, but the same safeguards can "slow, pause, or stop legitimate work," including defensive security tasks.S1 On data, Atlassian states only the data returned by an invoked MCP tool is sent to OpenAI, Astra supports Zero Data Retention for eligible API customers, enterprise access to Astra is off by default, and OpenAI is listed as a subprocessor that does not train on customer inputs or outputs.S1

Key numbers
MetricReported valueSource
MCP server daily callsMore than 15 million[S1]
MCP tool count exposed220-plus[S1]
Internal token reduction vs. prior serverUp to 25%[S1]
GPT-6 Astra input token price$10 per million tokens[S1]
GPT-6 Astra output token price$50 per million tokens[S1]
Spend-commitment counterpartyAtlassian to OpenAI (direction of payment)[S1]

Background timeline

  1. - Atlassian Intelligence launches, using OpenAI models from the start.S1
  2. - Original Atlassian-OpenAI partnership establishes the foundation later expanded.S1
  3. - Atlassian introduces its MCP integration for ChatGPT.S1
  4. - GPT-6 Astra ships as a standalone release.S1
  5. - Atlassian announces expanded OpenAI partnership and rebuilt MCP server, coinciding with Team '26 Europe.S1

XAIPART take

Technical impact

The MCP expansion turns Atlassian into a practical enterprise agent substrate: 220-plus tools across Jira, Confluence, Bitbucket, Loom and Goals, with per-user OAuth 2.1 + PKCE enforcement and tier-separated write/destructive actions that an admin can throttle or disable outright. For engineering teams already running Atlassian as a system of record, the 25% token reduction and the explicit DLP pipeline address the two biggest operational objections to long-running Rovo agents - cost and data egress - without forcing an all-in commitment to any single model family.XAIPART analysis

Market impact

Atlassian is paying OpenAI for priority model access while keeping Anthropic and other providers routed through the same gateway, which signals that model-portable enterprise infrastructure now has more commercial gravity than exclusive frontier-model deals. Buyers sourcing AI tooling should expect competing multi-model gateways from rival platforms, and any roadmap pinned solely to GPT-6 Astra will face the same benchmark ambiguity the source already flags on the Artificial Analysis Intelligence Index.XAIPART analysis

Action

Pilot the new MCP connection in a non-production Jira and Confluence tenant first, validate the OAuth 2.1 + PKCE enforcement and DLP labels against a representative prompt-injection scenario, and instrument Rovo credit usage per task before enabling Astra tier access. Lock the admin-console writes-disable switch and the per-scope read/write/search controls into your change-management baseline so that a model swap or an Astra safety pause cannot bypass your governance posture.XAIPART analysis

XAIPART Forecast

XAIPART expects that, within roughly two quarters of this announcement, at least one Atlassian-published Rovo reference architecture will demonstrate a third-party model performing greater than 50% of routed production traffic on the rebuilt MCP server, confirming the multi-model gateway as the durable layer rather than GPT-6 Astra. If, by , Atlassian has not disclosed a non-OpenAI model carrying more than 50% of Rovo traffic against this 15M-calls-per-day MCP baseline, this forecast is wrong.XAIPART analysis

Facts are as reported by the cited source. The design-in, sourcing and forward-looking statements above are XAIPART's analysis, not the source's claims. The contract size behind the "spend commitment," the precise scope of Astra Zero Data Retention eligibility, and whether the internal-Rovo model path matches the ChatGPT/Codex MCP retention terms are not disclosed by the source.

Corrections: none at publication. This brief will be updated with a timestamp if the source corrects its report.

Dated developments, extracted from this page's timeline (curated milestones = hollow markers).
Timeline of dated developmentsDated entries: 2023-04-01 2023 - Atlassian Intelligence laun…; 2023-01-01 - Original Atlassian-OpenAI partne…; 2025-12-01 2025 - Atlassian introduces its MC…; 2026-09-03 - GPT-6 Astra ships as a standalon…; 2026-10-06 - Atlassian announces expanded Ope….2023-04-012023 - Atlassian Intelligence laun…2023-01-01- Original Atlassian-OpenAI partne…2025-12-012025 - Atlassian introduces its MC…2026-09-03- GPT-6 Astra ships as a standalon…2026-10-06- Atlassian announces expanded Ope…

대체품 및 수명 주기

등록된 대체품 — 카탈로그 범위이며 시장 순위가 아닙니다
부품관계수명 주기근거
— 등록된 대체품 없음 데이터 필요 — 요구 사항 match_type 어떤 전임자 라벨이 표시되기 전에

"전임자" 및 "대체품" 라벨은 기록된 일치 유형, 수명 주기 상태 또는 출처 텍스트에서만 부여됩니다. 일치가 기록되지 않은 경우 라벨이 표시되지 않습니다. 당사 자체 등록 상품은 시장 기준이 아닙니다.

영향받는 부품

카탈로그 일치 없음. 이 보도는 현재 XAIPART에 등록된 어떤 부품과도 매핑되지 않습니다. 일치를 추론하지 않으며 자리 표시자 목록도 표시하지 않습니다.

차원별 비용 압력

Source: FRED · Generated · reference output z and composite are algorithm outputs, not a fetch snapshot

Cost pressure by dimension — composite stateDiverging bars for three dimensions around a zero midpoint. Input Cost has no reading; Supply Demand z -1.4711, notable; Fx Energy z 0.2546, neutral. Composite index -9.1, band neutral.0Input costno readingSupply/demandz −1.4711 · notable46 dFX & energyz +0.2546 · neutral5 dcomposite −9.1 · neutral−100 · −40 · −15 · 0 · +15 · +40 · +100
Underlying values — copyable for verification.
DimensionFRED series IDUnitLagAs of
Input costPCOPPUSDM, PALUMUSDM, PNICKUSDMUSD/mt52 d
Supply/demandPCU334413334413, IPG3344Sindex(1982=100) / index(2017=100)46 d
FX & energyDEXCHUS, DCOILBRENTEU, DHHNGSPrate / USD/bbl / USD/MMBtu5 d

No free authoritative interface for: gold · silver · rare earth · polysilicon · lithium carbonate · market share — listed rather than approximated.

이 콘텐츠의 제작 방식

프로세스 증거 — 수집, 출처 온전성, 모델 및 게이트
이 브리프의 감사 추적
Source fetched VentureBeat · venturebeat.com · 8,210 chars
Source sanity (S1) ok — passed before any model call (no s1_ block recorded)
Model / prompt MiniMax-M3 · prompt Blog Agent - News Summary (v2.8-final) · 8,006 tokens · 33.4s · run completed
Gate verdict hold · 5/6 applicable checks passed · spec v2.9 · C10 ratio 0.010471 · C10 rounds 0
Time contract 7 <time datetime> values in this brief — 0 violations (+08:00 or date-only)

위의 모든 행은 파이프라인에서 생성되며 수작업으로 작성되지 않습니다.

편집 점수

결정론적 게이트 결과 — 순수 PHP로 판정에 모델이 관여하지 않음
게이트 점수 분석 6 적용 가능한 검사, 5항목 통과: 83 %. Hold items: C15 (four views + no restating) — sent to human review. Gate spec: v2.9 (S0 + S1 + C1–C20) · Source affinity (C20): 0.8343. 적용 가능한 검사 통과 5 / 6 = 83% · 판정: hold Hold items: C15 (four views + no restating) — sent to human review Gate spec: v2.9 (S0 + S1 + C1–C20) · Source affinity (C20): 0.8343 게시 여부는 게이트가 결정합니다. 독립 감사 점수는 권고용일 뿐입니다.

독립 감사 (권고 사항이며 게시에 영향을 주지 않음): 51/100 · 등급 C — 상세

관련 보도

오류를 발견하셨습니까? 잘못된 점을 알려 주십시오 — 정정 사항은 원문과 함께 게시되고 기록됩니다. 기사를 조용히 수정하지 않습니다.

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출처

  1. Atlassian deepens its OpenAI partnership while keeping its platform multi-model — https://venturebeat.com/orchestration/atlassian-deepens-its-openai-partnership-with-a-spend-commitment-but-its-platform-stays-firmly-multi-model · rss · 조회일

사실은 S1/S2로 표시되며 링크된 출처로 추적됩니다. 다음 라벨이 붙은 구절은 분석 는 보도된 사실과 분리되어 유지되는 XAIPART의 자체 추론입니다. 출처 링크는 추정하지 않고 실제로 확인합니다. nofollow — 출처 표기는 의도적입니다.