Ataccama’s MCP Server, available now in the Databricks Marketplace, extends trusted data context from source systems through the Databricks platform to AI models and agents
BOSTON, June 16, 2026 (GLOBE NEWSWIRE) -- Ataccama, the data trust company, today announced a native integration with Databricks, the Data and AI company, to bring data quality, lineage, and governance signals from enterprise source systems, including SAP, Oracle, and mainframe environments, into the Databricks platform, helping customers build AI applications and agents on trusted data. Available now in the Databricks Marketplace, the integration connects Ataccama’s governed quality signals and metadata context directly to Databricks pipelines, workflows, and AI tools through the Ataccama MCP Trust Layer.
Enterprise AI has exposed a critical requirement for trusted data. As organizations consolidate data and AI workloads on platforms like Databricks, they need confidence not only in where data resides, but also in its quality, governance, and lineage. Without that context, AI outputs become difficult to explain and even harder to trust. A risk committee may reject a recommendation, a regulator may ask for documentation that cannot be produced, or a business leader may find themselves acting on results no one can confidently validate.
The MCP integration is now available on the Databricks Marketplace. Databricks Marketplace is an open marketplace for data, analytics and AI, powered by OpenSharing. Together, Ataccama and Databricks address the full infrastructure that production AI requires. Ataccama operates as the trust layer, validating that data is accurate, complete, and certified before it reaches Databricks, so the business definitions, metrics, and relationships that Unity Catalog Semantics governs are built on data that can actually be relied on. A semantic layer defines meaning precisely, but it cannot guarantee that the underlying data reflects reality. Ataccama closes that gap, so every agent, model, and analyst working inside Databricks reasons from definitions that are both well-governed and verifiably correct, from the source systems that supply the data through to the AI outputs that depend on it.
“The next phase of enterprise AI will be defined by trust,” said Jay Limburn, Chief Product Officer at Ataccama. “The organizations that succeed with AI will be the ones that can understand, govern, and stand behind the data informing every decision. By bringing trusted data context directly into Databricks via Databricks Marketplace, we're helping customers build the confidence needed to scale AI from promising pilots to business-critical outcomes.”
“Customers consistently ask us for easier, more secure ways to discover, access, and share data and AI assets across their organizations and ecosystems,” said Stephen Orban, SVP, Product Ecosystem & Partnerships at Databricks. “By bringing Ataccama ONE to the Databricks Marketplace, we’re helping our joint customers accelerate innovation and unlock more value from their data on an open, governed platform.”
Key capabilities include:
- Data trust signals are accessible to AI agents. Ataccama’s MCP Trust Layer exposes a combined semantic and quality layer to AI agents operating in Databricks, surfacing business glossary terms, catalog metadata, and quality scores so agents understand what a data asset means and where it came from, alongside live quality scores, monitoring results, and anomaly signals so they can assess whether it can be trusted before they act on it.
- Quality checks that run natively on Databricks compute. Ataccama translates enterprise data quality rules into SQL and executes them through Spark pushdown directly on Databricks clusters, without moving data into a separate processing environment. This enables non-technical users to create data quality rules and validate billions of records at the scale required for enterprise AI and analytics workloads.
- Pipeline gates that stop bad data before it reaches AI. Ataccama's Data Quality Gates integrate directly with Databricks Lakeflow and DLT pipelines, evaluating data at defined checkpoints before it advances to the next layer. Quality rules and thresholds are defined once in Ataccama ONE and enforced automatically at each gate. Changes propagate across pipelines without requiring code updates. Records that fail a threshold are flagged, quarantined, or rerouted for remediation, ensuring downstream systems receive only trusted data.
- An audit trail from source systems to AI outputs. Ataccama automatically scans source systems and captures lineage from Oracle, SAP, mainframes, and other enterprise environments through the Databricks platform to BI reports and regulatory outputs. Quality scores are recorded at each step, and full cross-system lineage – including systems outside Databricks that Unity Catalog cannot reach – is visible in a single interface.
- Governance that follows the data, not the platform. Organizations can extend governance policies, stewardship processes, and metadata management across Databricks and upstream enterprise source systems across more than 200 connectors spanning mainframe and legacy environments, as well as platforms such as dbt and AWS Glue. Organizations define standards once, and Ataccama enforces them wherever data lives, moves, or is used.
Ataccama will showcase the integration at Databricks Data + AI Summit 2026, taking place June 15–18 in San Francisco, at Booth #143.
The integration is now available on the Databricks Marketplace. Organizations that want to see it in their own environment can request a demo at ataccama.com.
About Ataccama
Ataccama provides the only end-to-end data trust platform that accelerates successful AI outcomes, mitigates risk, and powers data modernization with speed and scale. The Ataccama ONE platform is the essential data trust layer in the modern AI stack, sitting between data sources and AI orchestration to ensure every decision, model, and agent runs on accurate, governed, and trusted data. The platform unifies market-leading data quality and observability with catalog, lineage, and reference data to help organizations streamline their data management tech stack. The embedded ONE AI Agent acts as a digital data steward, continuously monitoring and improving data reliability, maximizing time-to-value, and team efficiency. Recognized as a 2026 Boston Business Journal Best Places to Work honoree, an Inc. Best Workplace for 2026, and a Leader in the 2026 Gartner Magic Quadrant™ for Augmented Data Quality, the 2026 Forrester Wave™ for Data Quality Solutions, and the 2025 Magic Quadrant™ for Data and Analytics Governance, Ataccama helps the world’s leading enterprises trust their data so they can accelerate AI. Learn more at www.ataccama.com.
Media contact
Lauren Ruth
Director of Global Communications
lauren.ruth@ataccama.com
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