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Agent Serve · Databases integration
Query and manage Azure Data Explorer (Kusto) clusters with KQL
Azure Data Explorer is a Databases integration for Agent Serve, the AI workspace where teams build and deploy AI agents. Agent Serve's Azure Data Explorer integration provides 14 Azure Data Explorer tools that AI agents can use inside Agent Serve's visual workflow builder. Azure Data Explorer connects with an API key. Explore deployment options with the Agent Serve team.
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Run Kusto Query Language queries against Azure Data Explorer and Fabric Eventhouse clusters, discover databases, tables, and schemas, push small batches of rows inline, and run management commands. Authenticates with a Microsoft Entra service principal using client credentials, so no interactive sign-in is needed.
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 an Azure Data Explorer block onto the workflow builder, and paste in your Azure Data Explorer API key.
Pick the tool you need, wire in an AI agent for reasoning or data transformation, and run. Your Azure Data Explorer automation is live.
14 Azure Data Explorer tools available in Agent Serve.
Run a Kusto Query Language (KQL) query against an Azure Data Explorer database and return the primary result table.
List the databases on an Azure Data Explorer cluster that the service principal can access.
List the tables in an Azure Data Explorer database, with their folder and docstring.
Read the column schema of an Azure Data Explorer table in CSL form (e.g., "Timestamp:datetime,Level:string"). Use this before writing a KQL query against an unfamiliar table.
Read the full schema of an Azure Data Explorer database as a flat list of every table and column, so an agent can discover the data model in one call.
Read size, row count, hot-cache footprint, and effective policies for a table — or for every table in the database when no table is given. Use it to see how much data a table actually holds before querying it.
List the stored functions in an Azure Data Explorer database, with their parameters and bodies, so an agent can reuse existing logic instead of rewriting it.
Push rows directly into an Azure Data Explorer table with .ingest inline. Data is parsed as CSV against the table schema unless an ingestion property says otherwise. Intended for small batches — use queued or streaming ingestion for production volumes.
Materialize the result of a KQL query into a table with .set, .append, .set-or-append, or .set-or-replace. Use this to build rollup or summary tables instead of pushing rows from a workflow. Kusto matches the query result to the target table by column type and position, NOT by column name, so project the columns in exactly the table's order or the data lands in the wrong columns.
Create a table in an Azure Data Explorer database from a CSL column schema. Succeeds without changing anything if a table of the same name already exists.
Drop a table from an Azure Data Explorer database. This permanently deletes the table and its data, and returns the tables that remain.
List ingestion failures recorded for a database, with the failing table, error code, root cause detail, and whether the failure is permanent or transient. Failures are retained for 14 days.
Check the state of administrative operations on a cluster, such as an async ingestion. Given an operation ID it returns that operation latest update; with no ID it returns the operations from the last two weeks.
Run an Azure Data Explorer management command (a control command starting with ".") such as .show, .create, .alter, or .drop. Write commands change cluster state permanently; use the Query operation for reads.
Ready-to-use templates featuring Azure Data Explorer. Click any to build it instantly.
Agent Serve's Azure Data Explorer integration adds 14 Azure Data Explorer tools to the AI agents you build in Agent Serve's visual workflow builder — you build it all visually. Query and manage Azure Data Explorer (Kusto) clusters with KQL. Teams often pair Azure Data Explorer with Affinity and incident.io in the same agent.
Agent Serve is available to teams by invitation. Request access and the team will map out the Azure Data Explorer agents, connections, and team access your process needs.