P2P

P E E R T O P E E R M A G A Z I N E · S P R I N G 2 0 2 6 87 If machine-consumable legal guidance is invoked programmat- ically, firms must carefully define contractual boundaries, disclaim- ers, privilege, and professional indemnity implications. Second, standards evolve uneven- ly. MCP may gain broad adoption, fragment, or coexist with alterna- tive protocols. History suggests that we rarely settle on a single standard for a given purpose. Firms should therefore avoid over- committing to any one protocol without preserving architectural flexibility. In practical terms, this means retaining the ability to fall back to conventional APIs on a case-by-case basis. The strategic focus should remain on the governed knowledge layer itself. Protocols may change, but structured, defensible intellectual capital retains value. THE NEW OPERATING MODEL So, is MCP a magic potion? In my view, it clearly is not. A protocol alone cannot transform legal services. Is it therefore merely old wine in new bottles? That depends on context, but I believe it is more than that. If firms treat MCP as another con- nector layered onto fragmented knowledge estates, its impact will be incremental. If firms invest in structured, gov- erned knowledge layers and use interoperable standards to connect them, the operating model shifts. In that shift: • Foundation models become interchangeable reasoning engines. • Knowledge layers become strategic assets. • Interoperability becomes a coordination mechanism. • High-judgment advisory remains premium. The durable strategic asset is the governed knowledge layer. MCP is the emerging interface that determines who can access it, how, and on whose terms. Under those conditions, MCP is not hype; it is a boundary technology in a broader architectural transition. And in that transition, the firms that own and govern their knowledge layer will be best positioned to shape, rather than react to, the next phase of legal service delivery. GABRIEL KARAWANI Gabriel Karawani is Co-Founder of ClearPeople and co- creator of Atlas, an intelligent knowledge platform built on Microsoft 365 and Azure. For over two decades, he has worked at the intersection of knowledge management, information architecture, and enterprise technology, helping law firms and professional services organizations design AI-ready knowledge environments. Gabriel's work focuses on a central premise: Outcomes are determined less by AI model sophistication and more by the quality, structure, and governance of the underlying knowledge layer. He advises firms on how to move from fragmented collaboration environments to governed, structured knowledge architectures that support Microsoft 365 Copilot, Azure AI, and emerging interoperability standards such as Model Context Protocol (MCP). Through ClearPeople's partnership with Microsoft, Gabriel works closely with product and engineering experts across Microsoft 365, Azure AI Search, and Azure AI Foundry. His practical experience includes helping organizations rationalize SharePoint estates, implement metadata and taxonomy discipline, design multi-source retrieval architectures, and establish governance frameworks that balance innovation with risk control. Gabriel is a frequent contributor to industry discussions in legal and professional services. His recent writing and panels have explored topics including AI readiness and knowledge foundations, multi-source AI knowledge orchestration, governance at the AI boundary, and the emerging strategic importance of the governed knowledge layer in law firms. With a Master's degree in Engineering from DTU - Technical University of Denmark and executive education in AI from MIT Sloan School of Management, Gabriel brings both technical depth and operational perspective. He does not approach AI as a theoretical construct, but as an architectural and governance challenge that must be addressed before sustainable value can be realized.

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