With MCP, AI systems work with iManage content through governed, permission-bound requests rather than bulk export. Content is never replicated or stored in third-party AI data stores, ensuring iManage remains the single source of truth. All AI access, reading, or writing is authenticated and governed by existing iManage permissions and ethical walls. Every interaction is logged and auditable, giving organizations full visibility into how AI tools use their content and supporting compliance with regulatory and internal governance requirements.
Knowledge in Motion
Governed Knowledge. AI-ready.
iManage MCP Server securely connects governed iManage content to the AI tools you choose. Replace custom integrations with one open protocol, let AI both retrieve content and write work product back into the official record, and keep every action permission-bound and auditable as your AI strategy evolves.
Standardized AI connectivity
One MCP (Model Context Protocol) connection replaces multiple custom API integrations. Configure once and connect any MCP-compliant AI tool — reducing IT effort while avoiding vendor lock-in.
Access without bulk extraction
iManage customers can request that their AI vendors access their content via the iManage MCP Server rather than bulk exporting documents. Customers should work with their vendors to understand what data leaves iManage through the connection and how it is handled.
Governed & auditable access
All AI access, whether reading content or writing it back, is authenticated, permission-bound, and logged.
A single secure gateway between AI and iManage
MCP provides a standardized integration layer between iManage and AI systems. Instead of maintaining separate integrations per vendor, organizations deploy one secure endpoint that scales across current and future AI tools.
Open, vendor-neutral architecture
Built on an open protocol, MCP avoids dependency on any single AI ecosystem. Your AI strategy remains flexible, extensible, and resilient as new models and platforms emerge.
iManage stays the source
AI retrieves documents and writes new work product back under the user's existing iManage permissions. It can never see or change anything the user is not permitted to see or change. iManage logs every interaction.
Read and write, both governed
iManage MCP Server is a two-way connection. AI tools can retrieve content and write work product back, including drafting documents, filing them in the right workspace, and updating metadata, all under the same permissions, ethical walls, and audit logging that govern every other action in iManage. Agents are treated like any other team member: You control what they are permitted to see, do, and touch.
Grounded in your organization's knowledge
The iManage Context Fabric™ gives AI tools the knowledge, context, and controls to understand, act, and make trusted updates. Answers and output are grounded in your organization's own institutional knowledge, accumulated judgment, and prior work, improving accuracy and quality. Because AI-generated work product is written back into the official record, the context fabric strengthens with every matter.
Future-proof AI integration foundation
As AI adoption accelerates, MCP ensures your integration strategy compounds rather than fragments — eliminating the rebuild cycle as tools and models change.
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FAQs
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How does MCP keep content secure and governed?
MCP is vendor‑neutral and designed to work with any MCP‑compliant AI system, including generalist AI platforms and legal‑specific AI tools. These include Microsoft Copilot, Harvey, Legora, Thomson Reuters CoCounsel, Spellbook, ChatGPT Enterprise, Gemini Enterprise from Google Cloud, and Claude. Organizations can add, switch, or onboard new AI tools without building new integrations or re‑architecting their environment.
Can AI make changes to our content through MCP?
Yes. With iManage MCP Server, write actions follow the same rules as read access. The AI acts on behalf of the authenticated user, bound by that user's permissions and ethical walls, and every action is recorded. It can never do anything the user could not do themselves. Administrators control which AI tools and which users can write content back.
Is MCP suitable for regulated and highly governed environments?
Yes. MCP is designed for regulated organizations that require permission‑bound access, auditability, and strict control over where content resides. By keeping content in iManage and logging every AI interaction, MCP enables AI adoption without compromising governance or compliance.
Why not build custom API integrations for each AI tool?
Custom point‑to‑point integrations are costly, slow to build, and brittle as AI tools evolve. Each new AI system becomes a separate IT project. MCP replaces this with a single standardized connection that works across AI tools, reducing integration sprawl and future‑proofing AI adoption.
Making Knowledge Work
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