Skyflow Unveils Data Protection Layer for MCP, Fortifying Agentic AI Against Privacy Risks
As AI agents grow smarter and more connected, their appetite for real-world data is exploding. But with that comes a surge in privacy and compliance challenges—particularly when it comes to MCP, the Model Context Protocol rapidly becoming the connective tissue of agentic AI systems.
Enter Skyflow, a data privacy infrastructure startup with a track record in AI security. Today, the company launched its MCP Data Protection Layer, purpose-built to secure sensitive data as it flows through MCP-enabled systems in SaaS platforms and enterprises.
With AI agents increasingly wired into databases, CRM systems, and third-party apps, Skyflow’s offering arrives at a critical moment—bridging the security gap between utility and compliance.
“AI agents are only as helpful as the data they can access,” said Anshu Sharma, CEO of Skyflow. “But that data often includes PII, PHI, and other regulated information. Skyflow protects it—without slowing agents down.”
MCP: The New AI Integration Standard—And Its Risk Frontier
First introduced by Anthropic and now supported by OpenAI, AWS, and Google, MCP standardizes how AI agents connect to tools and data sources without developers needing to write custom integration code. Think of it as the API bridge for AI workflows.
But this new bridge opens a privacy Pandora’s box: data like health records, financial info, and personal identifiers can flow unchecked through MCP servers—unless properly secured.
Skyflow’s solution tackles that risk head-on.
Smarter Than Traditional DLP
Traditional Data Loss Prevention (DLP) tools tend to be blunt instruments—blocking sensitive data outright or stripping functionality along the way.
Skyflow’s polymorphic data protection engine works differently. It dynamically masks, tokenizes, or rehydrates sensitive fields in real time, based on use case, policy, and user role. It’s context-aware, meaning it preserves the integrity of agent tasks without leaking data.
That’s especially crucial for agentic reasoning—where agents need to understand entity relationships or perform lookups across masked data without compromising security.
Two Deployment Models for Maximum Flexibility
Skyflow’s MCP protection comes in two flavors:
- MCP Gateway: A proxy layer that plugs into existing infrastructure, acting as a filter between MCP agents and backend data. No application rewrites required.
- MCP Server SDK: A developer toolkit for embedding privacy controls directly into agentic apps or MCP server implementations.
Both options ship with enterprise-grade features:
- Entity-preserving transformations to keep agent logic intact
- Field-level masking and redaction
- Role-based contextual rehydration
- Secure memory handling to prevent PII persistence
- Full audit logging for GDPR, HIPAA, and more
In short, it’s the granular privacy control MCP has been missing—without killing productivity.
Serving Data-Heavy Sectors at Scale
Skyflow sees immediate applicability for sectors like:
- Healthcare: where PHI access needs strict HIPAA-grade oversight
- Financial Services: balancing AI automation with PII protection
- Retail & Travel: where customer insights can’t come at the cost of compliance
- SaaS platforms: embedding AI without exposing customer data
This launch also fits into Skyflow’s broader AI security roadmap. It builds on earlier offerings like the Agentic AI Security and Privacy Layer and GPT Privacy Vault, as the company positions itself as the go-to privacy layer for AI-native platforms.
The Bigger Picture: Securing the Agentic Future
As AI agents move from novelty to necessity, companies face a new question: how do you let agents access sensitive data—without leaking it?
Skyflow’s answer is clear: inject privacy at the protocol layer, not just the app layer.
By anchoring data protection directly into the MCP pipeline, Skyflow is giving enterprises and developers a way to embrace agentic AI without fearing compliance violations, PR disasters, or accidental data exposure.
With major platforms like OpenAI, Anthropic, and AWS doubling down on MCP, Skyflow’s timing couldn’t be better—and its value proposition couldn’t be clearer.
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