Komprise, the leader in analytics-driven unstructured data management, today announced Komprise Universal File MCP to solve the growing problem of Model Context Protocol bloat which complicates search and user experience. The new solution delivers curated, streamlined access to unstructured data across hybrid storage silos, enhancing AI's value while reducing costs and improving accuracy.
As nearly every vendor publishes a MCP interface, AI is getting overloaded with multiple tool definitions, resulting in lower accuracy, slow performance and higher costs. The problem compounds with unstructured data response bloat as file and object listings are unbounded and can be millions to billions of files across disparate hybrid storage.
MCP, while standardizing connections between corporate data sources and AI tools, hasn't solved the widespread data readiness problem. Only 5% of enterprises say their data is ready for AI, according to a recent global survey of 10,000 businesses from Dun & Bradstreet. McKinsey's Enterprise AI FinOps Survey reveals that 60% of agentic AI computing costs are consumed by response refinement token loops.
Komprise Universal File MCP is a single interface for AI agents and LLMs to query across enterprise file storage, NAS, cloud, and unstructured data silos. It right-sizes responses by sending just the right unstructured data, enriched with context and governed by user-specific access permissions.
Key capabilities include governed secure access with authenticated responses based on user privileges and auditing, consistent schema leveraging petabyte-scale Global Metadatabase, high-quality enriched data via Komprise AI Preparation & Process Automation, noise filters through Deep Analytics to remove irrelevant and duplicate data, progressive disclosure with Transparent File Tables as Apache Iceberg tables, tiered data support via Transparent Move Technology, and intelligent ingest into AI, lakehouses and analytics for follow-up actions.
Example use cases include enterprise search where clinicians can find pathology images by study and time range using enriched DICOM metadata, data for agentic AI to execute multi-step workflows like drafting contract templates from liability clauses, and IT diagnostics and self-help for discovering non-compliant files or tiering research data.
The solution enables complex questions and workflow initiation while ensuring access controls remain intact, lifting the veil on dark enterprise data by unifying governed access across silos. This approach simplifies curation of unstructured data for AI across NAS, object and cloud storage rather than a single vendor footprint.
About Komprise
Komprise connects unstructured data management with AI through a unified platform. With Komprise Intelligent Data Management, enterprise IT can easily analyze, migrate, transparently tier, and manage the lifecycle of petabytes of file and object data across hybrid environments. Organizations gain full visibility across silos to optimize storage, backup, ransomware, and cloud costs. Smart Data Workflows and the Global Metadatabase unlock rich unstructured data context and governed access for AI.
