For Agents
Generate realistic synthetic test data in JSON, CSV, SQL, XML, or TXT formats and pull saved Mockaroo datasets and downloads.
Get started with Mockaroo 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:
"generate fake JSON test data"
# → Jentic returns the GET /events tool with parameter schema, agent executes.What an agent can do with Mockaroo API API.
Generate fake data in JSON via /api/generate.json with a custom field schema
Generate the same dataset as CSV, SQL, TXT, or XML through /api/generate.csv, /api/generate.sql, /api/generate.txt, or /api/generate.xml
Run a fully custom format using a Mockaroo template at /api/generate.custom
Inspect the catalogue of supported field types via /api/types
GET STARTED
Use for: I need to generate 100 fake user records as JSON, Generate a CSV of synthetic transactions for load testing, Get the list of Mockaroo field types I can use in a schema, Retrieve a saved Mockaroo dataset by name
Not supported: Does not handle production data anonymisation, database hosting, or schema migrations — use for generating synthetic test data only.
Mockaroo generates realistic synthetic test data on demand in JSON, CSV, TXT, SQL, and XML formats so engineers can populate development environments, run load tests, or seed analytics pipelines without using real customer data. The API exposes 11 endpoints covering field type metadata, multi-format generation, saved schemas under /api/datasets, and downloadable result files. Authentication is by API key in either the X-API-Key header or a key query parameter.
Reference a saved schema by name through /api/datasets/{name}
Retrieve a previously generated download by ID at /api/downloads/{id}
Authorise requests with an API key in either header or query parameter form
Patterns agents use Mockaroo API API for, with concrete tasks.
★ Seed test data for a development database
Engineers seed a development database by POSTing a field schema to /api/generate.sql and capturing the returned INSERT statements, or by calling /api/generate.json and importing the result into the application directly. The same schema can be replayed across CI runs to give every environment a consistent baseline of synthetic data.
POST a 5-field schema to /api/generate.sql with count=500 and a target table name, capture the INSERT statements, and run them against the dev database.
Load testing fixtures
Performance engineers generate large CSV or JSON fixtures via /api/generate.csv and /api/generate.json to drive load tests against APIs and analytics pipelines. The format flexibility means the same logical dataset can be rendered for whichever ingestion path the load test exercises, without rebuilding the schema each time.
Call /api/generate.csv with count=10000 and a custom schema, save the response to fixtures.csv, and feed it to the load test runner.
Saved dataset replay for QA
QA teams reference a saved Mockaroo schema through /api/datasets/{name} so the same well-known fixture can be regenerated on demand for regression tests. Combined with /api/downloads/{id} for previously generated files, this gives QA a stable, reproducible test data surface across environments.
GET /api/datasets/'customer_baseline' to regenerate the saved customer dataset, and store the response under tests/fixtures/customer_baseline.json.
Agent integration via Jentic
An AI assistant building test harnesses can search Jentic for 'generate fake JSON test data', load the /api/generate.json schema, and execute the call without ever holding the Mockaroo API key. The agent can then write the response straight into a fixtures directory and trigger downstream tests.
Search Jentic for 'generate fake JSON test data', load the /api/generate.json schema, execute it for 50 records using the 'user' field set, and write the result to fixtures/users.json.
11 endpoints — mockaroo generates realistic synthetic test data on demand in json, csv, txt, sql, and xml formats so engineers can populate development environments, run load tests, or seed analytics pipelines without using real customer data.
METHOD
PATH
DESCRIPTION
/api/types
List supported field types
/api/generate.json
Generate JSON synthetic data
/api/generate.csv
Generate CSV synthetic data
/api/generate.sql
Generate SQL INSERT statements
/api/generate.xml
Generate XML synthetic data
/api/generate.custom
Generate output using a custom Mockaroo template
/api/datasets/{name}
Reference a saved dataset by name
/api/downloads/{id}
Retrieve a previously generated download
/api/types
List supported field types
/api/generate.json
Generate JSON synthetic data
/api/generate.csv
Generate CSV synthetic data
/api/generate.sql
Generate SQL INSERT statements
/api/generate.xml
Generate XML synthetic data
Three things that make agents converge on Jentic-routed access.
Credential isolation
Mockaroo API keys are stored in the Jentic MAXsystem vault. Agents never see the X-API-Key value or the 'key' query parameter; Jentic injects the credential at execution time.
Intent-based discovery
Agents search Jentic for intents like 'generate fake JSON test data' or 'generate SQL insert statements' and Jentic returns the matching /api/generate.* operation with its input schema, including the field-type vocabulary.
Time to first call
Direct Mockaroo integration: a few hours to wire the API key, schema payload, and per-format endpoints. Through Jentic: under 30 minutes for the first call once the key is vaulted.
Alternatives and complements available in the Jentic catalogue.
FakeJSON API
Lightweight fake JSON data generator with a smaller field type catalogue
Choose FakeJSON for very simple ad-hoc JSON generation; choose Mockaroo when you need saved schemas, multiple output formats, or larger row counts.
GitHub REST API
Source control API used to commit Mockaroo-generated fixtures into a test repo
Use GitHub alongside Mockaroo when the agent needs to commit generated fixtures into a repository as part of a test harness setup.
OpenAPI Generator API
Generate client SDKs that consume the data Mockaroo produces
Pair OpenAPI Generator with Mockaroo when scaffolding both the API client and a synthetic dataset to test it against.
Specific to using Mockaroo API API through Jentic.
What authentication does the Mockaroo API use?
Mockaroo accepts an API key in the X-API-Key header or as the 'key' query parameter on each request. Through Jentic the API key is held in the MAXsystem vault and injected automatically; the agent never sees the raw key.
Can I generate SQL INSERT statements directly?
Yes. POST your schema to /api/generate.sql with the desired row count and table name and Mockaroo returns the INSERT statements ready to run against a target database. The same schema can be reused at /api/generate.json or /api/generate.csv to switch formats.
What are the rate limits for the Mockaroo API?
Limits are tied to the Mockaroo plan rather than the OpenAPI specification: the free tier permits 200 requests per day with up to 1,000 rows per call, and paid plans raise both ceilings. Confirm current limits at mockaroo.com/docs.
How do I generate JSON test data through Jentic?
Run pip install jentic, search Jentic for 'generate fake JSON test data', load the /api/generate.json schema, and execute it with your field schema and row count. Jentic injects the API key and returns the JSON payload to the agent.
Can I save a schema and reuse it across runs?
Yes. Save the schema under a name in the Mockaroo UI, then call GET /api/datasets/{name} to regenerate the same fixture on demand from the API. This is the recommended path for repeatable QA fixtures.
Is the Mockaroo API free to use?
Mockaroo offers a free tier capped at 200 daily API calls and 1,000 rows per call; higher volumes require a paid plan. Get started with Jentic at https://app.jentic.com/sign-up.
/api/generate.custom
Generate output using a custom Mockaroo template
/api/datasets/{name}
Reference a saved dataset by name
/api/downloads/{id}
Retrieve a previously generated download