aid: mckinsey-and-company name: McKinsey & Company description: >- McKinsey & Company is the senior partner of the MBB triumvirate of global strategy and management consulting firms, founded in 1926 by James O. McKinsey and headquartered in New York City. The firm operates from 130-plus cities across more than 65 countries with roughly 38,000-45,000 people serving corporations, governments, and not-for-profit organizations. McKinsey delivers through industry practices and cross-cutting capability practices: Strategy & Corporate Finance, Operations, Marketing & Sales, Risk & Resilience, Sustainability, Transformation, Implementation, Organization (formerly OrgSolutions), Growth / Marketing / Sales, McKinsey Digital, and McKinsey Technology. McKinsey Digital houses QuantumBlack (the AI division acquired in 2015), Leap (venture / business building), and the Technology practice. Internal generative-AI tooling is consolidated in Lilli, a McKinsey-built consultant assistant launched in August 2023 that indexes 100,000+ internal documents and is used by tens of thousands of firm employees. Research and thought leadership are published through McKinsey Insights, McKinsey Quarterly (the firm's flagship business journal since 1964), McKinsey Global Institute (MGI, the firm's business and economics research arm), the QuantumBlack AI report and State of AI survey, industry-specific reports, podcasts (The McKinsey Podcast, McKinsey Talks Operations, etc.), and the McKinsey on Books series. McKinsey does not publish a public commercial developer API or developer portal; all software the firm releases publicly flows through GitHub. The official `github.com/mckinsey` organization hosts a focused open-source portfolio centered on data, AI, and agentic systems — Vizro (low-code Plotly/Dash data-visualization toolkit), Agents-at-Scale ARK (Kubernetes-native framework for portable agentic applications), Agents-at-Scale Marketplace (curated Helm-chart catalog of ARK executors, MCP servers, and tools), CausalNex (Bayesian-network causal-reasoning library), QuantumBlack Design System (shadcn-based React component registry), and qbstyles (QuantumBlack Matplotlib themes). Kedro, the production-grade data and ML pipeline framework originally built inside QuantumBlack, was donated to the Linux Foundation (LF AI & Data) and is now governed at `github.com/kedro-org`. kind: company image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg tags: - Consulting - Management Consulting - Strategy - Professional Services - MBB - Big Three - AI - Data Science - Digital Transformation - Operations - Research - Insights - Open Source - Agentic AI - Kubernetes - Data Visualization - Causal Inference - QuantumBlack - Lilli - Industry Analysis url: https://raw.githubusercontent.com/api-evangelist/mckinsey-and-company/refs/heads/main/apis.yml created: '2026-05-23' modified: '2026-05-23' specificationVersion: '0.19' apis: [] common: - type: DomainSecurity url: security/mckinsey-and-company-domain-security.yml - type: Blog url: https://www.mckinsey.com/insights/rss - type: Website url: https://www.mckinsey.com/ - type: About url: https://www.mckinsey.com/about-us - type: Capabilities name: McKinsey Capabilities (cross-cutting practices) url: https://www.mckinsey.com/capabilities - type: Industries url: https://www.mckinsey.com/industries - type: KnowledgeCenter name: McKinsey Insights url: https://www.mckinsey.com/featured-insights - type: KnowledgeCenter name: McKinsey Quarterly url: https://www.mckinsey.com/quarterly/overview - type: KnowledgeCenter name: McKinsey Global Institute (MGI) url: https://www.mckinsey.com/mgi/overview - type: Hub name: McKinsey Digital url: https://www.mckinsey.com/capabilities/mckinsey-digital/how-we-help-clients - type: Hub name: QuantumBlack, AI by McKinsey url: https://www.mckinsey.com/capabilities/quantumblack/how-we-help-clients - type: Hub name: McKinsey Technology url: https://www.mckinsey.com/capabilities/mckinsey-digital/how-we-help-clients/mckinsey-technology - type: Hub name: Leap by McKinsey (business building) url: https://www.mckinsey.com/capabilities/leap/how-we-help-clients - type: Hub name: McKinsey Sustainability url: https://www.mckinsey.com/capabilities/sustainability/how-we-help-clients - type: Tools name: Lilli (internal generative-AI assistant) url: https://www.mckinsey.com/about-us/new-at-mckinsey-blog/meet-lilli-our-generative-ai-tool - type: Podcast name: The McKinsey Podcast url: https://www.mckinsey.com/featured-insights/mckinsey-podcast - type: GitHubOrganization name: McKinsey (official) url: https://github.com/mckinsey - type: GitHubOrganization name: Kedro (LF AI & Data, originated at QuantumBlack) url: https://github.com/kedro-org - type: GitHubRepository name: Vizro (low-code data-visualization toolkit) url: https://github.com/mckinsey/vizro - type: GitHubRepository name: Agents-at-Scale ARK (Kubernetes-native agentic framework) url: https://github.com/mckinsey/agents-at-scale-ark - type: GitHubRepository name: Agents-at-Scale Marketplace url: https://github.com/mckinsey/agents-at-scale-marketplace - type: GitHubRepository name: CausalNex (Bayesian-network causal reasoning) url: https://github.com/mckinsey/causalnex - type: GitHubRepository name: QuantumBlack Design System url: https://github.com/mckinsey/quantumblack-design-system - type: GitHubRepository name: qbstyles (QuantumBlack Matplotlib themes) url: https://github.com/mckinsey/qbstyles - type: GitHubRepository name: Kedro (production-grade data and ML pipelines) url: https://github.com/kedro-org/kedro - type: LinkedIn url: https://www.linkedin.com/company/mckinsey - type: X url: https://x.com/McKinsey - type: YouTube name: McKinsey & Company url: https://www.youtube.com/@McKinsey - type: Careers url: https://www.mckinsey.com/careers - type: Alumni url: https://www.mckinsey.com/alumni - type: PrivacyPolicy url: https://www.mckinsey.com/privacy-policy - type: TermsOfService url: https://www.mckinsey.com/terms-of-use - type: Contact url: https://www.mckinsey.com/contact-us - type: Features data: - name: McKinsey Insights and McKinsey Quarterly description: McKinsey Insights aggregates the firm's research and commentary; 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not exposed as a public API. - type: Compliance data: - name: GDPR description: European personal-data processing aligns with the EU General Data Protection Regulation. - name: SOC 2 description: McKinsey-managed digital products and managed-services environments operate under SOC 2-type controls. - name: ISO 27001 description: McKinsey's information-security management aligns with ISO 27001 controls. - name: Client Confidentiality description: All engagements operate under master consulting agreements with strict confidentiality and conflict-management terms; the firm's professional standards are central to its IP and engagement protocols. properties: - type: JSONLD url: https://raw.githubusercontent.com/api-evangelist/mckinsey-and-company/refs/heads/main/json-ld/mckinsey-and-company-context.jsonld - type: Vocabulary url: https://raw.githubusercontent.com/api-evangelist/mckinsey-and-company/refs/heads/main/vocabulary/mckinsey-and-company-vocabulary.yml - type: Plans url: https://raw.githubusercontent.com/api-evangelist/mckinsey-and-company/refs/heads/main/plans/mckinsey-and-company-plans-pricing.yml - type: RateLimits url: https://raw.githubusercontent.com/api-evangelist/mckinsey-and-company/refs/heads/main/rate-limits/mckinsey-and-company-rate-limits.yml - type: FinOps url: https://raw.githubusercontent.com/api-evangelist/mckinsey-and-company/refs/heads/main/finops/mckinsey-and-company-finops.yml plansReconciled: false rateLimitsReconciled: false finopsReconciled: false position: Consuming maintainers: - FN: Kin Lane email: kin@apievangelist.com