You can already quickly scale privacy work with Vera, DataGrail’s AI agent, from right inside your privacy platform. When Vera detects cookies across your site, you can categorize them in bulk using Vera’s recommendations, rather than one by one. When a risk assessment is due, Vera pulls in real system metadata to generate a working first draft, so you’re reviewing and refining rather than starting from a blank page.
But the most effective privacy teams today aren’t working in just one tool. If your organization has leaned into AI adoption, you’re likely already spending much of your day in tools like OpenAI or Claude to get work done faster. The DataGrail MCP lets you bring Vera’s deep context about your privacy program into those workflows, so you can kick off privacy work, pull real program data, and take action without switching contexts.
That’s what the DataGrail MCP Server is for. The MCP can:
- Share information from DataGrail with other tools and unique artifacts
- Help you troubleshoot via the DataGrail knowledgebase
- Directly take action on key privacy tasks without entering DataGrail at all
Whether you’re just starting to build AI into your workflows or already running complex multi-tool automations, the DataGrail MCP meets you where you are. “Read” tools are an easy entry point: pull program insights, surface system data, and get Vera’s context directly in your AI client of choice, no extra setup required. As you get more comfortable, “write” tools open up powerful new possibilities, letting you take action in DataGrail from wherever you’re already working.
Let’s talk through what that changes for you and how to get started.
What is an MCP and how do you configure it?
MCP (Model Context Protocol) is an open standard that lets AI tools connect to external applications and take real actions inside them. An MCP allows separate AI agents to communicate, effectively creating instant integrations not only with Open AI or Claude, but with any AI agent you use that also offers an MCP.
Vera has full context on your program: your systems, your processing activities, your consent environment, your uploaded documentation. That context is what makes a “write” action useful rather than risky. A generic AI writing to your privacy platform is a liability. With the DataGrail MCP, you can add Vera to the team of any agentic privacy work you’re doing across platforms, and Vera’s full understanding of your privacy operations with it.
The DataGrail MCP Server is available for all DataGrail Enterprise Plan Customers. Check with your account manager if you’re unsure of your access. When you’re ready, you don’t need so much as a line of code to get your MCP set up.
Even if your account has the MCP enabled, all users don’t immediately have access to all functionality by default. In particular, the ability to write using the MCP, or update DataGrail in real-time via your AI agent(s), must be provisioned by a system administrator from your organization.
When should you use the MCP?
If the privacy work you’re focused on requires a lot of context switching between platforms, or involves a team that aren’t regular DataGrail users, the MCP should be your first port of call. The right starting point depends on your company culture and personal preferences. If you’re newer to AI, start with read-only use cases like generating privacy program reporting. As you get more confident, you can expand into more powerful “write” actions across cookie management, risk assessments, and more. Here are a few examples across the spectrum.
Reporting
Vera can generate reporting insights on the spot, including tables and graphs, from right inside DataGrail. But if you’re working on a big report, you might want to apply your brand color scheme, translate graphics to a slide deck, or even create an interactive Claude artifact with your data.
Bringing DataGrail reporting insights to OpenAI or Claude only requires access to the relevant functionality in DataGrail and “read” permissions for the MCP.
Cookie Management
For larger organizations facing hundreds to thousands of uncategorized cookies, manual consent management is not practical. Vera already offers the option to detect and categorize cookies in bulk using strategic and contextual recommendations.
However, if you already monitor your cookies for other projects using AI, creating a new cookie rule can be as simple as describing your general idea to Claude or OpenAI if you’re using the DataGrail MCP, and your rules can be applied instantly.
Risk Assessments
Many savvy privacy teams already use ChatGPT or Claude for DPIA automation. But using Vera to autofill assessments instead provides the benefit of a far richer draft using real system data. That said, you might already have a system or skills you like for completing risk assessments in your AI client of choice.
Connect your AI client to the DataGrail MCP and you can continue drafting risk assessments in your preferred platform with your existing customizations and the added context from DataGrail, and your work can relay to DataGrail in real-time. Your risk assessment draft then moves directly into the defined workflow and risk tracking infrastructure of your organization.
Project Management
While DataGrail offers many task management features to keep teams organized on DSR management, assessment progress, and data mapping, some partners might prefer to work in tools like Asana or Jira that they use for other crossfunctional work.
Depending on your desired configuration, you can use the DataGrail MCP’s read functions or read and write functions to stand up a mirror image of task progress across platforms using a scheduled task in Cowork and the MCP of both platforms, or by wiring up a custom integration with Claude Code. You could even configure automated nudges over Slack when tasks are running behind.
How does the DataGrail MCP actually change privacy work?
Let’s walk through a day in the life of someone using the DataGrail MCP. You’ve just been flagged on a new processing activity and need to kick off a DPIA. Normally, you’d open DataGrail, find the right template, start the assessment, pull in the relevant systems, and begin working through the questions, probably with several browser tabs open for reference. With MCP write tools enabled, you describe the activity in Claude and ask Vera to spin it up.
The assessment is created from the right template, the relevant systems are already linked, and Vera begins populating responses based on your uploaded documentation and a metadata catalog of 12,000+ systems. You review, accept, edit, or regenerate answers as you go. When you’re done, you’ve got a draft that reflects your actual program, not a blank template.
The same access lets you update existing assessments on the fly: changing a due date, moving status forward, marking something ready for review. Work that normally means navigating to a specific field in the platform happens in a sentence.
The data map tells a similar story. When a new system is detected in your tech stack, it’s tempting to put it in a backlog to address later, but ideally the system should be associated with the right processing activities to ensure your Record of Processing Activities is up-to-date. With the MCP, you can set up a notification and prompt Claude for more information, then pass to Vera when you’re ready to finalize your edits. For teams that want their data map to reflect reality rather than the last time someone had a free afternoon for cleanup, that kind of frictionless update matters a lot.
When shouldn’t you use the MCP?
The DataGrail MCP is designed to keep you in the driver’s seat when answers are unclear or mistakes are irreversible. Approving a final assessment, deciding whether a processing activity presents acceptable risk, publishing changes to a live consent banner without human review: those decisions belong to the people who hold the context and the accountability for them. The MCP makes execution faster, not judgment optional.
One thing worth knowing: everything done through the DataGrail MCP is fully logged. Every write action, every tool invocation, every access change. If your program requires that level of traceability, it’s there by default.
Next steps
If you’re a DataGrail customer, the DataGrail MCP is available now. Connect via Claude or your AI tool of choice, and talk to your account manager if you need help getting started.
If you’re new to DataGrail, request a demo to see how Vera and the MCP fit into the broader platform.
