As organizations accelerate their adoption of AI tools — from Microsoft Copilot to Harvey, Claude, and ChatGPT Enterprise —the challenge isn’t just about adopting the latest technologies. It’s about creating a unified, secure and scalable approach to accessing the critical and sensitive content held within their enterprise systems.
Enter, stage right: Model Context Protocol (MCP).
The Model Context Protocol (MCP) is a game-changer for organizations looking to harness the full potential of AI across their enterprise. By standardizing how AI tools connect to data and content sources, MCP dramatically reduces integration complexity and accelerates deployment. It empowers orchestrators like ChatGPT, Harvey, and Claude to seamlessly interact with iManage content while preserving security and governance. This scalable, future-ready approach ensures that as AI tools evolve, law firms and legal departments can continue to innovate securely and with confidence, making MCP a strategic investment for long-term agility and growth.
What Is Model Context Protocol (MCP)?
Model Context Protocol is a universal open standard created by Anthropic in 2024 that enables AI models (like Claude or GPT-4) to securely connect with enterprise applications and workflows through an orchestration layer such as Microsoft Copilot or Chat GPT Enterprise. With MCP, AI models can plug into existing systems using a consistent protocol, minimizing friction and IT overhead. It eliminates the need for custom integrations between AI tools and enterprise systems, streamlining deployment and reducing time-to-value.
For legal professionals the promise of MCP sits squarely in their need for unique and specialized workflows without compromising security. By enabling AI players to interact fluidly MCP unlocks new use cases and adaptive workflows in real time while users and content remain governed and secure in iManage.
Why iManage chooses MCP as its preferred protocol layer
By implementing Model Context Protocol (MCP), iManage, the leading document and email management platform, unlocks a powerful foundation for scalable, intelligent access across the platform. iManage remains the secure trusted foundation that connects and governs content across the AI ecosystem. Most importantly, MCP positions iManage for long-term innovation, ensuring compatibility with evolving AI models and tools while maintaining leadership in secure, AI-enabled knowledge work.
“When the integration tax disappears, imagination becomes the bottleneck.”
I recently spoke with Kristin Calve from CCBJ about how we are entering the second act of AI — a phase that is more dynamic, open, and simultaneously multi-tool. It will change the way we work, but crucially, it is a technical change that enables a knowledge worker dividend as it puts better work practices and tangible AI utility directly into the tools they are already comfortable using.
MCP enables iManage to shift from a proprietary integration model to an open ecosystem architecture whilst maintaining security and governance, which fundamentally changes how legal technology innovation occurs.
Rather than requiring each AI vendor to build custom, proprietary connectors through traditional API libraries to access iManage content for their customers, MCP establishes a standardized protocol that allows any AI solution to connect rapidly to the iManage platform. This approach ensures that AI tools operate within the firm’s governance framework, not outside it.
It also contributes to the strength of the iManage Partner network whereby the interoperability of integrations from the full range of Partner developed tools, or those developed in house by law firms, can work in tandem with our Platform.
When we all standardize on an integration and interoperability method, we can focus more on product innovation and less on building integration infrastructure.
At iManage, we are already seeing customers develop new workflows and rapidly deploy new ways of working to the workforce by taking advantage of the MCP connection between iManage Work and generative AI tools. This is neither hype nor hypotheticals, but delivering real knowledge outcomes with technology today.
Fewer IT nerves, more of a central nervous system for legal AI
This open AI ecosystem model enables rapid experimentation and deployment of emerging AI capabilities while maintaining centralized governance and security; essentially democratizing access to the rich content in iManage while preserving control over the firm's most valuable asset.
When legal IT leaders and AI vendors develop their technology infrastructure roadmaps, MCP represents a fundamental architectural choice: interoperability by design. Rather than building point-to-point connections with custom connectors and APIs between systems, or creating data silos, MCP enables a hub-and-spoke model where your knowledge management platform becomes the secure foundation from which any compatible application can be leveraged.
This shifts infrastructure planning from "What systems do we integrate?" to "What capabilities do we want to enable?" Your technology stack becomes more modular and adaptable, allowing you to swap out applications, test new solutions, or build custom tools without major architectural changes.
“That shift creates space for law firms and vendors to reimagine what their tools can do, who they can partner with, and how they can deliver value,” writes Antti Innanen and Elias Ylönen for Artificial Lawyer in the article What Is MCP and Why You Need It.
Traverse Legal, in their article MCP and the Future of AI Integration: What Founders Need to Know, writes how “MCP takes a different path. Instead of interpreting frontends, it enables direct, structured calls to application functions.”
“Think of it (MCP) as teaching the AI the language of the app itself.”
MCP goes beyond the call and response of a typical chat with an AI interface, opening the opportunity for multiple tools to simultaneously act upon LLM outputs in chat interfaces and put the work to work. This gets to the dynamism of how it operates.
Key benefits of iManage’s use of MCP for the legal industry
✅ Security & compliance
MCP and the iManage knowledge work platform ensures that sensitive work product remains within the firm’s secure environment. No external indexing, no shadow repositories.
✅ Operational efficiency
One integration supports many AI tools. IT teams deploy faster and maintain less.
✅ Future-proofing
MCP is designed to evolve with AI. As new models emerge, they can plug into the same protocol.
✅ User trust
Answers are grounded in firm-approved content, not generic internet data.
✅ Governance assurance
As iManage makes the knowledge work platform accessible via MCP, it respects ethical walls, access controls, and audit trails — critical for legal compliance.
MCP and iManage in action: A real-world use case
Customers gain flexibility from an AI open partner ecosystem and MCP support. As iManage continues to scale its 300-strong open partner network, the company supports rising demand in AI collaboration while fostering deep partnerships with leading technology providers.
As a result, iManage customers will be able to deploy AI applications and intelligent agents that autonomously orchestrate workflows across multiple systems. Instead of knowledge workers manually switching between disconnected applications, AI agents can intelligently coordinate and action their tasks.
Here is a very simple but powerful example of a use case:
Legal document analysis (leases) demonstration
What we did
We used iManage AI search to find lease documents in the M007 Pipeline Project Finance Deal matter, then processed the data into a visual dashboard.
Steps taken
- Document search: Asked iManage to find all lease agreements in the matter
- Data extraction: Pulled key information (tenants, amounts, dates) from the 11 identified lease documents
- Currency conversion: Used XE.com to convert ZAR amounts to USD to normalize the currencies
- Dashboard creation: Had the LLM build a simple visualization showing portfolio overview, dates, financials, and timelines
- Calendar integration: Created Outlook events for upcoming lease start dates that were placed in calendars for awareness of impending actions
Technical components
- iManage search for document discovery
- Web scraping for live exchange rates
- React dashboard for data visualization
- Microsoft Outlook integration for calendar events
Result
- A consolidated view of 11 lease agreements totalling $1.8 M annual revenue
- Automated calendar reminders for key dates and direct links back to source documents in iManage
- A dashboard entirely derived from the data enshrined in those lease agreements.
The goal is to guide AI to discover available content and capabilities in iManage, while respecting existing user permissions, governance, and access controls.
The end user outcome? Simplified synthesizing of information and the augmentation of the tools and humans delivering better work at scale.
Reshape your interconnected knowledge work with AI Confidence™
MCP isn’t just a technical protocol — it’s a strategic foundation for AI Confidence.
MCP offers a transformative opportunity in that it breaks down integration barriers, allowing AI to discover and interact with content across platforms securely and efficiently. This opens the door to new workflows, partnerships, and services that were previously too complex or too costly to implement.
For CIOs, legal IT leaders and AI strategy leaders adopting MCP means:
- Reducing risk
- Accelerating innovation
- Empowering knowledge professionals
- Maintaining control over the firm’s most valuable asset: its work product
As AI continues to reshape workflows, MCP compatibility ensures that your firm stays ahead — securely, intelligently, and confidently — with your content grounded in iManage Work.
Ladies and Gentlemen, please take your seats for Act II of AI: Making knowledge work by putting knowledge in motion.
Making Knowledge Work
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About the author
Paul Walker
Paul Walker is Global Solutions Director at iManage, where he helps define and deliver solutions that bring advanced technology and AI into practical use for law firms, corporate legal teams, and other knowledge-intensive organizations. With more than 20 years’ experience across legal practice, professional services, and enterprise technology, Paul works at the intersection of data, compliance, and knowledge management. His background includes senior roles at PwC, Slaughter and May, Autonomy, and HP, giving him a unique perspective on how to turn emerging technologies into tools that streamline workflows, strengthen governance, and unlock institutional insight.