Recommender API

Name: Recommender API API
Brand: Recommender API
Availability: InStock

✓ Official Vendor SpecCloud InfrastructureComputeoauth212 EndpointsREST

For Agents

Fetch Google Cloud cost, security, and performance recommendations for projects and folders, and update each recommendation's lifecycle state as agents act on them.

Quickstart

Get started with Recommender API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"list google cloud recommendations"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with Recommender API API.

List active recommendations for a project, folder, or organization filtered by recommender type and location

Mark a recommendation as claimed, accepted, succeeded, failed, or dismissed to track agent-driven remediation

Retrieve insights that explain the underlying signals behind a Google Cloud recommendation

Update recommender configuration to enable or disable specific recommendation types per scope

GET STARTED

Start building with Recommender API API

Explore with Jentic

View OpenAPI Document

Use for: List all idle VM recommendations in my Google Cloud project, Get the cost-saving recommendations for the production folder, Mark a recommendation as accepted after the underlying change has been applied, Find IAM rightsizing recommendations across all locations in this organization

Not supported: Does not apply changes to underlying Google Cloud resources, surface billing invoices, or provision new infrastructure — use for retrieving and updating the lifecycle of recommendations and insights only.

The Google Cloud Recommender API surfaces machine-learning-driven recommendations and insights about Google Cloud resources, helping teams optimize cost, security, performance, and reliability across projects, folders, and organizations. It exposes recommenders for areas such as idle VM detection, IAM role rightsizing, and commitment utilization, and lets clients mark recommendations as claimed, accepted, succeeded, failed, or dismissed to track lifecycle. Insights and recommendations are scoped per location and recommender type, with full IAM-controlled access and audit visibility.

Use Cases

Patterns agents use Recommender API API for, with concrete tasks.

★ Automated cost optimization sweep

Run a recurring agent that lists idle VM and rightsizing recommendations across every project in an organization, applies the suggested change through the Compute Engine API, and then marks each Recommender recommendation as succeeded so it stops appearing in dashboards. Combining listing, IAM-scoped filtering, and lifecycle marking lets cloud teams reclaim spend without manual review.

List recommendations under projects/my-prod/locations/us-central1/recommenders/google.compute.instance.IdleResourceRecommender, apply each, then call markSucceeded on every applied recommendation.

Continuous IAM rightsizing

An agent enumerates IAM policy recommendations under each project, evaluates the suggested role reductions against an internal allow-list, applies safe changes via the IAM API, and marks accepted recommendations claimed and then succeeded. This closes the loop between detection and remediation for least-privilege enforcement.

List google.iam.policy.Recommender recommendations for projects/finance-prod, mark each as CLAIMED, apply the role changes, and call markSucceeded on completion.

Security insight triage

Surface insights from security-focused recommenders into a triage queue, enrich them with the explanatory metadata returned from the insights endpoint, and let an agent dismiss low-value findings while escalating high-severity ones to a ticketing system. Each lifecycle change is recorded against the Recommender API so reporting stays consistent.

Iterate insights under projects/my-prod/locations/global/insightTypes/google.iam.policy.Insight, post HIGH severity items to PagerDuty, and call markAccepted on the rest.

Agent-driven cloud governance through Jentic

An AI agent built on Jentic discovers Recommender operations by intent, loads the schema for listing and lifecycle endpoints, and runs a governance loop that pulls recommendations, applies safe ones, and marks them succeeded. Credentials stay isolated in Jentic's vault so agents never see raw OAuth tokens.

Search Jentic for 'list google cloud recommendations', load the Recommender list schema, execute against projects/my-prod, then call markSucceeded for each handled recommendation.

Key Endpoints

12 endpoints — the google cloud recommender api surfaces machine-learning-driven recommendations and insights about google cloud resources, helping teams optimize cost, security, performance, and reliability across projects, folders, and organizations.

METHOD

PATH

DESCRIPTION

GET

/v1beta1/{+parent}/recommendations

List recommendations for a parent scope and recommender

GET

/v1beta1/{+parent}/insights

List insights for a parent scope and insight type

POST

/v1beta1/{+name}:markAccepted

Mark a recommendation as accepted

POST

/v1beta1/{+name}:markClaimed

Mark a recommendation as claimed by an actor

POST

/v1beta1/{+name}:markSucceeded

Mark a recommendation as succeeded after applying

POST

/v1beta1/{+name}:markDismissed

Dismiss a recommendation so it no longer appears

GET

/v1beta1/recommenders

List available recommender types

GET

/v1beta1/insightTypes

List available insight types

GET

/v1beta1/{+parent}/recommendations

List recommendations for a parent scope and recommender

GET

/v1beta1/{+parent}/insights

List insights for a parent scope and insight type

POST

/v1beta1/{+name}:markAccepted

Mark a recommendation as accepted

POST

/v1beta1/{+name}:markClaimed

Mark a recommendation as claimed by an actor

POST

/v1beta1/{+name}:markSucceeded

Mark a recommendation as succeeded after applying

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Google OAuth 2.0 client credentials and refresh tokens for the Recommender API are stored encrypted in the Jentic vault. Agents receive scoped, short-lived access tokens at execution time and never see the underlying secret material.

Intent-based discovery

Agents search Jentic with intents like 'list google cloud recommendations' or 'mark recommendation accepted' and Jentic returns the matching Recommender operation with its full request schema, so the agent calls the correct endpoint without browsing the discovery document.

Time to first call

Direct integration with the Recommender API through Google's discovery client takes 2-3 days for OAuth setup, scope wiring, and lifecycle handling. Through Jentic the same flow is under 1 hour: search, load, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Cloud Monitoring API

Pairs raw Cloud Monitoring metrics with Recommender's distilled optimization advice.

Choose Monitoring when the agent needs raw time-series data; choose Recommender when it needs an actionable suggestion.

Complementary

Cloud Asset API

Provides asset inventory that contextualizes the resources Recommender targets.

Use Cloud Asset to enumerate resources first, then feed the inventory into Recommender lookups.

Complementary

Cloud Billing Budgets API

Adds budget thresholds that pair with Recommender cost-saving signals.

Use Billing Budgets for spend caps; use Recommender to identify what to trim under those caps.

Alternative

Cloud Billing API

Surfaces raw billing detail without machine-learned remediation suggestions.

Choose Cloud Billing for invoice and SKU data; choose Recommender for prescriptive optimization actions.

FAQs

Specific to using Recommender API API through Jentic.

What authentication does the Recommender API use?

The Recommender API uses Google OAuth 2.0 with the cloud-platform scope, declared as the Oauth2 and Oauth2c security schemes in the spec. Through Jentic, OAuth tokens are stored encrypted in the Jentic vault and exchanged at call time, so agents never receive raw refresh tokens or service account keys.

Can I mark recommendations as accepted or dismissed with the Recommender API?

Yes. The API exposes lifecycle endpoints at /v1beta1/{+name}:markAccepted, :markClaimed, :markSucceeded, :markFailed, and :markDismissed. Each call requires the etag from the most recent get to avoid concurrent updates, and the response contains the updated state record.

What are the rate limits for the Recommender API?

Google Cloud applies per-project quotas to the Recommender API; the standard default is 600 read requests per minute per project, with mutating mark calls counted against the same pool. Quotas can be increased through the Cloud Console quotas page once a project has demonstrated steady usage.

How do I list cost recommendations for a project through Jentic?

Search Jentic for 'list google cloud recommendations', load the schema for GET /v1beta1/{+parent}/recommendations, and execute with parent set to projects/PROJECT/locations/LOCATION/recommenders/google.compute.instance.IdleResourceRecommender. Jentic returns the parsed recommendation list with etags ready for follow-up mark calls.

Is the Recommender API free?

The Recommender API itself is free to call within Google Cloud quotas; you pay only for the underlying resources whose recommendations you act on, such as Compute Engine VMs or IAM-managed services. There is no per-recommendation charge for retrieval or lifecycle updates.

Which recommenders and insight types can I enumerate?

Calling GET /v1beta1/recommenders and GET /v1beta1/insightTypes returns the full registry, including google.compute.instance.IdleResourceRecommender, google.iam.policy.Recommender, and google.cloudbilling.commitment.SpendBasedCommitmentRecommender, among others. Use these identifiers in subsequent list calls.