Microsoft Azure DataLakeAnalyticsCatalogManagementClient
Browse all Azure APIs41
AI ReadinessFoundational (D-)41/100
Agent-ready OpenAPI document · curated by JenticStorageDatabasenone45 EndpointsREST
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For Agents
Browse and inspect the U-SQL catalog of an Azure Data Lake Analytics account - list databases, tables, views, schemas, assemblies, and ACLs, and manage credential entries.
Use for: List all U-SQL databases in a Data Lake Analytics account, Get the schema definition for a specific table in a U-SQL database, Retrieve table statistics for a Data Lake Analytics table, Find all stored procedures defined in a U-SQL database
Not supported: Does not submit U-SQL jobs, manage Data Lake Analytics accounts, or read raw lake files - use for U-SQL catalog metadata and credential management only.
Jentic publishes the only available OpenAPI specification for DataLakeAnalyticsCatalogManagementClient, keeping it validated and agent-ready. The API exposes the U-SQL catalog of an Azure Data Lake Analytics account so callers can browse and inspect databases, schemas, tables, views, table-valued functions, stored procedures, assemblies, credentials, and ACLs. It is read-oriented over the catalog plus credential mutation endpoints, and is the path agents use to discover the shape of analytics data before submitting jobs. All 45 operations live under the /catalog/usql/* path tree.
Install Jentic One Beta
Connect the DataLakeAnalyticsCatalogManagementClient to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the DataLakeAnalyticsCatalogManagementClient, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fazure.com%2Fdatalakeanalyticscatalogmanagementclient" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fazure.com%2Fdatalakeanalyticscatalogmanagementclient" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with DataLakeAnalyticsCatalogManagementClient API.
List U-SQL databases, schemas, tables, and views in a Data Lake Analytics catalog
Inspect table schemas, table statistics, partitions, types, and table-valued functions
Retrieve assemblies, stored procedures, and external data sources for a database
Read and modify catalog ACLs at account and database scope
Create, update, retrieve, and delete catalog credential entries used by U-SQL jobs
List and inspect packages and column-level statistics within a U-SQL database
Use Cases
Patterns agents use DataLakeAnalyticsCatalogManagementClient API for, with concrete tasks.
★ Pre-job catalog inspection
Before submitting a U-SQL job to Azure Data Lake Analytics, an analyst or agent inspects the target catalog to confirm tables, schemas, and types match the job script. The catalog API returns database, schema, table, and column metadata so the job author can validate references against the live catalog instead of a stale data dictionary.
List all tables in the database 'sales' on the Data Lake Analytics account and return the column list for the table 'orders'
Catalog credential management for U-SQL jobs
U-SQL scripts that pull from external systems (Azure SQL Database, blob, etc.) need credential entries registered in the catalog. The credentials endpoints let an automation flow create, rotate, and delete those entries against a specific U-SQL database without manual portal steps.
Create a catalog credential named 'sql-prod-reader' on database 'sales' with the supplied user identity and password, then verify it appears in the credential list
Catalog ACL audit
Compliance checks routinely verify which principals have access to U-SQL databases. The ACL list endpoints return the full set of ACL entries at account or database scope so an audit script can reconcile actual permissions against an expected access matrix.
Retrieve the ACL list for database 'finance' and flag any principal that is not in the approved auditor allowlist
Agent-driven analytics catalog discovery
An AI agent asked to answer a business question against Data Lake Analytics first needs to know what data exists. Through Jentic, the agent searches for catalog discovery operations, lists databases and tables, then composes a U-SQL query against the resolved schema. The catalog API is the agent's source of truth for what U-SQL objects exist.
Discover all tables in databases on the Data Lake Analytics account that contain a column named 'customer_id' and return their fully qualified names
Key Endpoints
45 endpoints — jentic publishes the only available openapi specification for datalakeanalyticscatalogmanagementclient, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
GET
/catalog/usql/databases
List U-SQL databases in the catalog
GET
/catalog/usql/databases/{databaseName}
Get a specific U-SQL database
GET
/catalog/usql/databases/{databaseName}/schemas/{schemaName}/tables
List tables in a schema
GET
/catalog/usql/databases/{databaseName}/credentials
List catalog credentials in a database
GET
/catalog/usql/databases/{databaseName}/acl
List ACL entries for a database
GET
/catalog/usql/databases/{databaseName}/assemblies
List assemblies registered in a database
GET
/catalog/usql/databases/{databaseName}/procedures
List stored procedures in a database
GET
/catalog/usql/databases
List U-SQL databases in the catalog
GET
/catalog/usql/databases/{databaseName}
Get a specific U-SQL database
GET
/catalog/usql/databases/{databaseName}/schemas/{schemaName}/tables
List tables in a schema
GET
/catalog/usql/databases/{databaseName}/credentials
List catalog credentials in a database
GET
/catalog/usql/databases/{databaseName}/acl
List ACL entries for a database
GET
/catalog/usql/databases/{databaseName}/assemblies
List assemblies registered in a database
GET
/catalog/usql/databases/{databaseName}/procedures
List stored procedures in a database
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
D
DataLakeAnalyticsCatalogManagementClient
- Foundational (D-)41/100
72
Foundational Compliance56
Developer Experience & Jentic Compatibility16
AI-Readiness & Agent Experience94
Agent Usability100
Security100
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
72
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: A-Signals: 4
86%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
0%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
100%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
56
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: CSignals: 4
0%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
25%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
16
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
66%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
0%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
0%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
100
Security
Trust, risk posture, and security compliance.
Grade: A+Signals: 1
100%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
100
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A+Signals: 1
100%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring the Azure Data Lake Analytics catalog by hand means resolving the per-account host from the {accountName}.{adlaCatalogDnsSuffix} template, obtaining an Azure AD bearer token for the Data Lake Analytics resource, and threading it onto every catalog call yourself. Through Jentic you install once, import Data Lake Analytics Catalog Management from the API Directory, store the Azure credential once, and your agent calls it.
Permission scoping
The catalog puts the database and schema names in the URL path (/catalog/usql/databases/{databaseName}/schemas/{schemaName}/...), so a rule can pin your agent to one database's metadata. You choose the operations it may call, so mutating ones like the credential create-or-delete endpoints are not included unless you add them, leaving the agent on read-only listing operations.
Credential isolation
Your Azure credential is stored once, encrypted, by your own Jentic One instance and injected as a scoped bearer token at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'list U-SQL databases' or 'get a table schema in Data Lake Analytics', and Jentic returns the matching catalog operation with its input schema so the agent inspects the catalog without scraping the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using DataLakeAnalyticsCatalogManagementClient API through Jentic.
Why is there no official OpenAPI spec for DataLakeAnalyticsCatalogManagementClient?
Microsoft Azure does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call DataLakeAnalyticsCatalogManagementClient via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.
What authentication does the Data Lake Analytics Catalog API use?
The catalog client itself reaches an account-specific endpoint (typically https://{accountName}.azuredatalakeanalytics.net) and is gated by Azure Active Directory bearer tokens issued for the Data Lake Analytics resource. Through Jentic, the AAD credential is held in the encrypted vault and a scoped token is supplied at execute time so the bearer token never enters the agent's prompt context.
Can I list all tables in a U-SQL database with this API?
Yes. Call GET /catalog/usql/databases/{databaseName}/schemas/{schemaName}/tables to enumerate tables under a specific schema, or use the per-database listing endpoints to walk schemas first. Combined with the table-detail endpoint you can retrieve column lists, partitioning, and statistics for each table.
What are the rate limits for the Data Lake Analytics Catalog API?
Azure Data Lake Analytics applies subscription-level throttling rather than per-endpoint rate caps; sustained polling against catalog list endpoints can return HTTP 429 responses with a Retry-After hint. Treat the catalog as a metadata store and cache results for the duration of a job rather than calling list operations on every step.
How do I rotate a U-SQL catalog credential through Jentic?
Search Jentic for 'rotate u-sql catalog credential', load the schema for PUT /catalog/usql/databases/{databaseName}/credentials/{credentialName}, then execute with the new credential payload. The pip install jentic Python SDK uses the async search, load, execute pattern and reads JENTIC_AGENT_API_KEY from your environment.
Is the Data Lake Analytics Catalog API free?
There is no separate charge for catalog metadata calls beyond standard Azure Data Lake Analytics pricing - you pay for the underlying account, storage, and any U-SQL job hours consumed. Catalog reads do not bill per-request.
Can I limit what my agent is allowed to do with the Azure Data Lake Analytics Catalog API?
Yes. Because Jentic One is self-hosted, you set the rules that decide which catalog operations and credentials your agent may use. Since the database and schema names sit in the URL path, such as /catalog/usql/databases/{databaseName}/schemas/{schemaName}, you can pin the agent to a single database's metadata. You also choose which operations it can call, so you can leave it on read-only listing endpoints like GET /catalog/usql/databases and exclude the credential create and delete operations unless you deliberately add them.
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