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Agent Serve · Databases integration
Manage records in Microsoft Dataverse tables
Microsoft Dataverse is a Databases integration for Agent Serve, the AI workspace where teams build and deploy AI agents. Agent Serve's Microsoft Dataverse integration provides 18 Microsoft Dataverse tools that AI agents can use inside Agent Serve's visual workflow builder. Microsoft Dataverse connects with one-click OAuth. Explore deployment options with the Agent Serve team.
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Integrate Microsoft Dataverse into your workflow. Create, read, update, delete, upsert, associate, query, search, and execute actions and functions against Dataverse tables using the Web API. Supports bulk operations, FetchXML, file uploads, relevance search, and table metadata lookup. Works with Dynamics 365, Power Platform, and custom Dataverse environments.
Agent Serve accounts are created by invitation. Request access for your team, or accept an invitation from your workspace admin, then sign in.
Open your workspace, drag a Microsoft Dataverse block onto the workflow builder, and connect your account with one-click OAuth.
Pick the tool you need, wire in an AI agent for reasoning or data transformation, and run. Your Microsoft Dataverse automation is live.
18 Microsoft Dataverse tools available in Agent Serve.
Query and list records from a Microsoft Dataverse table. Supports OData query options for filtering, selecting columns, ordering, and pagination.
Retrieve a single record from a Microsoft Dataverse table by its ID. Supports $select and $expand OData query options.
Create a new record in a Microsoft Dataverse table. Requires the entity set name (plural table name) and record data as a JSON object.
Update an existing record in a Microsoft Dataverse table. Only send the columns you want to change.
Create or update a record in a Microsoft Dataverse table. If a record with the given ID exists, it is updated; otherwise, a new record is created.
Delete a record from a Microsoft Dataverse table by its ID.
Create multiple records of the same table type in a single request. Each record in the Targets array must include an @odata.type annotation. Recommended batch size: 100-1000 records for standard tables.
Update multiple records of the same table type in a single request. Each record must include its primary key. Only include columns that need to be changed. Recommended batch size: 100-1000 records.
Execute a FetchXML query against a Microsoft Dataverse table. FetchXML supports aggregation, grouping, linked-entity joins, and complex filtering beyond OData capabilities.
Perform a full-text relevance search across Microsoft Dataverse tables. Requires Dataverse Search to be enabled on the environment. Supports simple and Lucene query syntax.
Execute a bound or unbound Dataverse action. Actions perform operations with side effects (e.g., Merge, GrantAccess, SendEmail, QualifyLead). For bound actions, provide the entity set name and record ID.
Execute a bound or unbound Dataverse function. Functions are read-only operations (e.g., RetrievePrincipalAccess, RetrieveTotalRecordCount, InitializeFrom). For bound functions, provide the entity set name and record ID.
Upload a file to a file or image column on a Dataverse record. Supports single-request upload for files up to 128 MB. Provide the file through the File input; its bytes are read from storage and sent as the raw request body.
Download a file from a file or image column on a Dataverse record. Stores the file in execution storage and returns a file reference, plus the base64 content and metadata directly.
Associate two records in Microsoft Dataverse via a navigation property. Creates a relationship between a source record and a target record. Supports both collection-valued (POST) and single-valued (PUT) navigation properties.
Remove an association between two records in Microsoft Dataverse. For collection-valued navigation properties, provide the target record ID. For single-valued navigation properties, only the navigation property name is needed.
Retrieve table (entity) and column (attribute) definitions for a Microsoft Dataverse table by its singular logical name. Use this to look up the correct entity set name and column logical names before building record data for other operations.
Retrieve the current authenticated user information from Microsoft Dataverse. Useful for testing connectivity and getting the user ID, business unit ID, and organization ID.
Ready-to-use templates featuring Microsoft Dataverse. Click any to build it instantly.
Agent Serve's Microsoft Dataverse integration adds 18 Microsoft Dataverse tools to the AI agents you build in Agent Serve's visual workflow builder — you build it all visually. Manage records in Microsoft Dataverse tables. Teams often pair Microsoft Dataverse with Rippling and Linear in the same agent.
Agent Serve is available to teams by invitation. Request access and the team will map out the Microsoft Dataverse agents, connections, and team access your process needs.