Google Cloud Datastore API
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AI ReadinessFoundational (D-)41/100
Official vendor OpenAPI document · agent-readyStorageDatabaseoauth218 EndpointsREST
For Agents
Read, write, query, and transact over entities in Cloud Datastore's NoSQL document database. Lets agents persist application state with strong consistency and ACID transactions.
Use for: I need to look up a Datastore entity by its key, Run a GQL query that returns the 10 most recent orders, Commit a transaction that updates two entities atomically, Allocate a new entity ID before inserting
Not supported: Does not run analytical SQL, manage relational schema, or stream change events - use for entity reads, writes, queries, and transactions in Datastore-mode databases only.
Cloud Datastore is Google's schemaless NoSQL document database for fully managed, scalable application storage. The API exposes 18 endpoints covering entity lookup, queries (GQL and structured), allocateIds for ID generation, and atomic transactions via beginTransaction, commit, and rollback. It also exposes import and export operations to and from Cloud Storage, plus index management for query optimisation.
Install Jentic One Beta
Connect the Cloud Datastore API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Cloud Datastore API, 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%2Fgoogleapis.com%2Fdatastore" | 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%2Fgoogleapis.com%2Fdatastore" | 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 Cloud Datastore API.
Look up entities by key in single calls or batched lookups
Run GQL and structured queries against entity kinds with filters and ordering
Commit groups of inserts, updates, upserts, and deletes in atomic transactions
Reserve entity IDs ahead of insert with allocateIds and reserveIds
Export and import entire entity kinds to and from Cloud Storage
Manage composite indexes that back complex query patterns
Use Cases
Patterns agents use Cloud Datastore API for, with concrete tasks.
★ Schemaless Application State Storage
Persist user profiles, sessions, and operational state in a NoSQL document store with strong consistency on lookups by key. The API's commit operation supports atomic upserts of multiple entities, and lookup batches reads to minimise round-trips. Most applications can replace a small relational store with Datastore in under a day if access patterns are key-based.
POST /v1/projects/{projectId}:lookup with a list of entity keys for users; POST /v1/projects/{projectId}:commit with mutations to upsert their session state
Atomic Multi-Entity Transactions
Begin a Datastore transaction, perform reads and writes, then commit or roll back atomically. POST /v1/projects/{projectId}:beginTransaction returns a transaction id that scopes subsequent lookups and the final commit. This supports use cases such as inventory decrement plus order creation in a single ACID step. Rollback on conflict is exposed as a first-class operation.
Begin a transaction, lookup the inventory entity, decrement its count, upsert an order entity, and commit; rollback on conflict
Backup and Restore via Cloud Storage
Export a Datastore kind to Cloud Storage as a managed backup, then re-import the same files into a different project for disaster recovery or environment refresh. POST /v1/projects/{projectId}:export and :import accept a Cloud Storage URI prefix and entity-filter for kinds and namespaces. Long-running operations let agents poll for completion.
POST /v1/projects/{projectId}:export with outputUrlPrefix gs://acme-backup/datastore/2026-06-10/ and entityFilter for kinds [User, Order]; poll the operation until done
AI Agent State Persistence
An AI agent that needs persistent state across runs can use Datastore through Jentic without operator-written client code. Jentic search returns the matching lookup, query, commit, or transaction operation, the agent loads the schema, and Jentic executes against datastore.googleapis.com using vault-stored credentials. This makes durable agent memory a single intent-search away.
Use Jentic to search 'commit a datastore mutation', load the commit schema, and execute it with an upsert mutation for the agent's state entity
Key Endpoints
18 endpoints — cloud datastore is google's schemaless nosql document database for fully managed, scalable application storage.
METHOD
PATH
DESCRIPTION
POST
/v1/projects/{projectId}:lookup
Look up entities by key
POST
/v1/projects/{projectId}:runQuery
Run a GQL or structured query
POST
/v1/projects/{projectId}:commit
Commit mutations atomically
POST
/v1/projects/{projectId}:beginTransaction
Begin a transaction
POST
/v1/projects/{projectId}:allocateIds
Allocate new entity IDs
POST
/v1/projects/{projectId}:export
Export entities to Cloud Storage
POST
/v1/projects/{projectId}:lookup
Look up entities by key
POST
/v1/projects/{projectId}:runQuery
Run a GQL or structured query
POST
/v1/projects/{projectId}:commit
Commit mutations atomically
POST
/v1/projects/{projectId}:beginTransaction
Begin a transaction
POST
/v1/projects/{projectId}:allocateIds
Allocate new entity IDs
POST
/v1/projects/{projectId}:export
Export entities to Cloud Storage
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.
C
Cloud Datastore API
- Foundational (D-)41/100
44
Foundational Compliance56
Developer Experience & Jentic Compatibility20
AI-Readiness & Agent Experience94
Agent Usability63
Security58
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
44
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: DSignals: 4
70%
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).
5%
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.
20
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
81%
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.
63
Security
Trust, risk posture, and security compliance.
Grade: B-Signals: 1
62%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
58
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: C+Signals: 1
58%
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 Cloud Datastore API by hand means setting up Google OAuth, refreshing short-lived scoped tokens rather than embedding client secrets, and addressing project-level operations on datastore.googleapis.com. Through Jentic you install once, import the Cloud Datastore API from the API Directory, store the Google credential once, and your agent calls it.
Permission scoping
The API carries the project id in the URL path (/v1/projects/{projectId}:runQuery and :commit), so a rule can pin your agent to one project. You choose the operations it may call, so it can look up entities and run queries while commit and export are not included unless you add them.
Credential isolation
Your Google OAuth credential is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'run a Datastore query' or 'commit a mutation', and Jentic returns the matching Cloud Datastore operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Cloud Datastore API through Jentic.
What authentication does the Cloud Datastore API use?
The Cloud Datastore API uses OAuth 2.0 with the datastore or cloud-platform scope. Through Jentic the OAuth client and refresh tokens are stored in your Jentic One instance and the agent receives short-lived scoped access tokens, so raw Google credentials never enter the agent context.
Can I run transactions with the Cloud Datastore API?
Yes. Call POST /v1/projects/{projectId}:beginTransaction to obtain a transaction id, perform lookups and queries with that id, then commit the mutations atomically with POST /v1/projects/{projectId}:commit, or roll back via :rollback. Conflicts on serializable transactions are surfaced and require client retry.
What are the rate limits for the Cloud Datastore API?
Google enforces standard Cloud quotas on datastore.googleapis.com: per-project read/write entity-operation quotas, transaction quotas, and admin operation limits for export and import. Quotas are visible in the Cloud Console under IAM and admin, quotas, filtered to datastore.googleapis.com.
How do I run a GQL query through Jentic?
Search Jentic for 'run a datastore gql query', load the schema for POST /v1/projects/{projectId}:runQuery, and execute it with gqlQuery.queryString set. Jentic returns the batch of entities and the cursor for paginated continuation.
Is the Cloud Datastore API free?
Datastore has a daily free tier (entity reads, writes, deletes, and a stored-data allowance). Beyond the free tier you pay per million entity operations and per GiB of stored data; see the official pricing page for current rates.
How do I export a Datastore kind to Cloud Storage?
Call POST /v1/projects/{projectId}:export with outputUrlPrefix as a gs:// URI and entityFilter listing kinds and namespaces. The response is a long-running operation; poll its name endpoint until done is true and metadata.outputUrlPrefix is set.
Can I limit what my agent is allowed to do with the Cloud Datastore API?
Yes. Jentic One is self-hosted, so your own rules decide which Cloud Datastore operations and credentials the agent may use. Because every call carries the project id in its path, such as POST /v1/projects/{projectId}:runQuery and :commit, you can pin the agent to a single project. You also choose the operations it may call, so it can look up entities and run GQL queries while commit, export, and rollback stay out of reach unless you grant them.
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