> For the complete documentation index, see [llms.txt](https://docs.ovaledge.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ovaledge.com/release8.2/hotfix-releases/release8.1.0.x/release8.1.0.4.md). # Release8.1.0.4 This release introduces key enhancements and bug fixes across the Model Context Protocol (MCP), Login, Lineage, and Load Metadata from Files, improving AI-assisted governance, access discovery, session management, lineage accuracy, and metadata onboarding. **Key Highlights** * **Model Context Protocol (MCP)** * Added a new access discovery capability that enables users to identify effective permissions for users, roles, and catalog objects through AI-assisted conversations, including inherited permissions and direct navigation to governed assets. * Introduced Critical Data Element (CDE) management through AI-assisted interactions, allowing users to add or remove CDE designations for supported assets while adhering to governance controls. * Added support for updating Custom Field values through natural language requests, enabling governed metadata enrichment across supported assets with validation, auditability, and direct asset navigation. * Introduced intelligent Data Quality Rule recommendations that analyze business context to suggest reusable rules, recommend suitable Data Quality functions and dimensions, and automatically create new rules when sufficient metadata is available. * **Login**: Fixed session timeout behavior to automatically redirect users to the login screen after inactivity, eliminating error messages and unnecessary notification sounds. * **Global Search**: Fixed an issue where some Data Catalog objects did not appear in search results or returned errors, ensuring all cataloged objects are consistently searchable and can be opened directly from the search results. * **Lineage**: Resolved incomplete lineage generation between Snowflake and Power BI by incorporating database names into object matching, ensuring accurate end-to-end lineage visibility. * **Load Metadata from Files (LMDF)**: Added support for creating sub-reports within Report Metadata templates, allowing users to preserve report hierarchies by defining multiple worksheets or tabs under a single parent report. **Release Details**:
Release TypeRelease VersionBuild <Release. Build Number. Release Stamp>Build Date
Hotfix ReleaseRelease8.1.0.4release8.1.0.4.81046268e6cJuly 03, 2026
## Model Context Protocol ### New & Improved **Discover Effective Object Access through MCP** A new MCP search-and-discovery tool (get\_user\_object\_access) is now available to help users understand access permissions configured in OvalEdge through AI-assisted conversations. Users can determine the effective permissions assigned to users, roles, and catalog objects without manually reviewing security settings across multiple areas of the platform. The tool provides a simple way to investigate object access while respecting existing access controls and governance policies. Users can: * Determine the effective access a specific user has on a supported catalog object. * Identify users and roles with access to a particular object, and review their assigned permissions. * Evaluate permissions granted directly to users and those inherited through assigned roles. * Resolve and return the highest effective permission available when access is derived from multiple sources. * Identify the roles contributing to inherited access permissions. * View metadata and data permissions associated with a user or object. * Validate users, assets, and supported object types before retrieving access details. * Navigate directly to the corresponding object in OvalEdge through a provided application link. The tool supports both user-centric and object-centric access discovery, enabling users to determine which specific user has access to an object or to identify who has access to a particular object and the permissions they possess. It also handles scenarios where no permissions are assigned and returns clear responses to help users understand access availability. **Critical Data Element Management through MCP** A new MCP governance action (update\_cde\_associations) is now available to help users manage Critical Data Element (CDE) designations through AI-assisted conversations. Users can mark supported catalog assets as CDEs or remove existing CDE designations without manually navigating the application. The tool provides a simple way to maintain business-critical assets while respecting existing governance controls and approval processes. Users can: * Mark supported catalog assets as Critical Data Elements. * Remove CDE designations from assets that are no longer considered business critical. * Update one or multiple assets in a single request. * Manage CDE associations using natural language prompts. * Receive guidance when additional information is required to identify the correct asset. * View the updated governance details and navigate directly to the affected asset via the provided application link. The tool validates user permissions, supported asset types, and existing CDE associations before applying updates. It also supports conversational clarification when multiple matching assets are found, helping users complete governance activities more efficiently while maintaining governance standards. **Custom Field Value Updates through MCP** A new MCP governance action (update\_custom\_field\_value) is now available to help users update Custom Field values through AI-assisted conversations. Users can enrich and maintain business-specific metadata without leaving their AI workflow, making metadata stewardship more efficient and reducing the need to navigate through multiple screens in OvalEdge. The tool provides a governed way to update Custom Field values while respecting existing access controls, permissions, and approval processes. Users can: * Update Custom Field values for supported assets via natural-language requests. * Modify one or multiple Custom Fields in a single request. * Update text, number, code, and date Custom Fields. * Update Custom Fields across supported assets, including tables, columns, files, reports, APIs, terms, tags, Data Quality Rules, and Data Products. * Receive guidance when additional information is required to complete an update. * Validate that Custom Fields are available and eligible for updates through MCP. * Navigate directly to the updated asset through a provided application link. The tool validates user permissions, Custom Field configurations, and input values before applying changes. It also ensures that only Custom Fields configured to allow API updates can be modified through MCP. All successful updates are captured in the audit trail with OE-MCP recorded as the source. **Data Quality Rule Recommendations through MCP** A new MCP governance action (data\_quality\_rule\_recommendation) is now available to help users identify, reuse, and create Data Quality Rules through AI-assisted conversations. Users can leverage existing business context, such as Business Descriptions, Business Rules, associated Terms, Custom Fields, and Critical Data Elements (CDEs), to accelerate Data Quality implementation and reduce manual effort. The tool provides an intelligent way to operationalize business requirements into Data Quality Rules while promoting consistency and reuse across the organization. Users can: * Discover CDEs using natural language prompts. * Retrieve Business Descriptions, Business Rules, associated Term descriptions, and relevant Custom Field values for identified objects. * Recommend suitable Data Quality Functions by analyzing the business intent captured in object metadata. * Identify existing Data Quality Rules that can be reused for similar business requirements. * Determine whether objects are already associated with existing Data Quality Rules. * Associate eligible objects with existing Data Quality Rules to avoid duplicate implementations. * Create new Data Quality Rules automatically when sufficient business context is available and no suitable rule exists. The rules are created based on the existing Data Quality Functions (System Function and Custom Function) * Generate rule purposes based on business descriptions, business rules, and associated terms. * Recommend and assign appropriate Data Quality Dimensions, such as Accuracy, Completeness, Validity, Consistency, Uniqueness, Timeliness, and Integrity. * Prevent duplicate rule creation by recommending reuse whenever equivalent validations already exist. * Return direct links to objects and Data Quality Rules for further review and management. The tool also validates that sufficient business context is available before creating new rules. If required validation details, such as input criteria, success criteria, thresholds, or business logic, are missing, the tool guides users to enrich the metadata before proceeding. ## Login ### Fixed **Automatic Redirection After Session Timeout** In the OvalEdge application, an issue where the application did not redirect to the login screen after a session expired due to inactivity has been resolved. Instead, clicking within the application after the session expired displayed an error message and triggered a notification sound. The application now redirects to the login screen when the session times out. ## Global Search ### Fixed **Fixed Search Issues for Data Catalog Objects** In Elasticsearch Search, an issue where some Data Catalog objects did not appear in search results even though they existed in the catalog has been resolved. Searches for certain objects returned an error instead of matching results, resulting in inconsistent data discovery. The search logic has been corrected to ensure that all cataloged objects are reliably returned and can be opened from the search results. ## Lineage ### Fixed **Resolved Incomplete Snowflake–Power BI Lineage** In Connectors | Build Lineage, an issue where lineage between Snowflake and Power BI displayed only temporary lineage instead of the complete lineage has been resolved. The lineage process did not consider the Snowflake database name when matching objects, which prevented complete lineage from being generated. The matching logic has been updated to include the database name, ensuring accurate lineage between Snowflake and Power BI assets. ## Load Metadata from Files ### New & Improved **Support for Creating Manual Reports Via Manual Connectors Through LMDF Templates** LMDF supported the bulk creation of Manual Reports using the Manual Connector and Report Metadata templates, but it did not allow defining sub-reports under a parent report. As a result, reports containing multiple worksheets or tabs had to be created as separate reports, making it difficult to preserve their natural grouping and hierarchy. With this enhancement, the LMDF Report Metadata template for the Manual Connector now includes a SubReport column, which allows users to create multiple sub-reports under a single parent Manual Report and map individual worksheets or tabs as sub-reports while maintaining the intended report hierarchy. *** Copyright © 2026, OvalEdge LLC, Peachtree Corners, GA, USA. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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