JSON Validator & Formatter — Validate, Prettify, Schema-Check at Scale

Validate JSON from URLs or direct input, catch syntax errors with exact line/position, optionally validate against a JSON Schema — all in one run. Bulk-validate thousands of API responses or data files in a single workflow.

Most JSON validation tools are one-payload-at-a-time UIs (jsonlint, jsonformatter.org). This actor is built for the other use case: validating hundreds of API responses at once, regressions in an ETL pipeline, or confirming every file in an S3 bucket is well-formed JSON before downstream processing.

Who uses this

• QA / API testers running nightly validation across 50+ API endpoints.
• ETL engineers gate-checking data between pipeline stages — bad JSON blocks before it corrupts a warehouse load.
• Integration architects auditing third-party API contracts — has the vendor changed the response schema?
• Security engineers fuzzing JSON endpoints and cataloging validation-error patterns.
• Developers / technical writers who need a programmable JSON playground for tutorials.

What you get per input

Field	Type	Example
input_source	string	URL or inline label
is_valid	boolean	true
error_message	string | null	"Unexpected token ',' at position 142"
error_line	number | null	5
error_column	number | null	17
parsed_size_bytes	number	4821
depth	number	4 (max nesting)
key_count	number	127
schema_valid	boolean | null	true (if JSON Schema supplied)
schema_errors	array | null	[{path, message, expected, got}]
formatted	string	Pretty-printed JSON
minified	string	Whitespace-stripped JSON
http_status	number | null	200 (if fetched from URL)
fetch_time_ms	number | null	180

Input

{
  "inputs": [
    { "type": "url", "value": "https://api.github.com/repos/vercel/next.js" },
    { "type": "url", "value": "https://httpbin.org/json" },
    { "type": "inline", "value": "{\"name\":\"test\",\"items\":[1,2,3]}" }
  ],
  "schemaUrl": "https://example.com/schemas/github-repo.json",
  "failOnSchemaMismatch": false,
  "autoFix": true,
  "requestTimeoutMs": 5000
}

• inputs — list of {type: "url"|"inline", value}. Bulk tested up to 1,000 inputs per run.
• schemaUrl — optional. If supplied, every parsed JSON is validated against this JSON Schema.
• failOnSchemaMismatch — set true to fail the run (useful as a CI gate).
• autoFix — attempt common fixes (trailing commas, unquoted keys, single quotes). Returns auto_fixed: true if applied.
• requestTimeoutMs — per-URL fetch timeout.

Python usage example

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "inputs": [
        {"type": "url", "value": "https://api.github.com/repos/vercel/next.js"},
        {"type": "url", "value": "https://jsonplaceholder.typicode.com/todos"},
        {"type": "inline", "value": '{"bad": "json",}'},  # trailing comma
    ],
    "autoFix": True,
}

run = client.actor("knotless_cadence/json-validator-formatter").call(run_input=run_input)
results = list(client.dataset(run["defaultDatasetId"]).iterate_items())

for r in results:
    status = "OK" if r["is_valid"] else "FAIL"
    print(f"[{status}] {r['input_source']:70s} depth={r['depth']} keys={r['key_count']}")
    if not r["is_valid"]:
        print(f"    ERROR: {r['error_message']} at line {r['error_line']}:{r['error_column']}")

CI gate pattern

Use as a pre-merge JSON-file validation gate:

curl -s "https://api.apify.com/v2/acts/knotless_cadence~json-validator-formatter/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"inputs":[{"type":"url","value":"https://raw.githubusercontent.com/owner/repo/main/config.json"}],"failOnSchemaMismatch":true,"schemaUrl":"https://raw.githubusercontent.com/owner/repo/main/config.schema.json"}' \
  | jq -e '.[0].is_valid and .[0].schema_valid' || {
    echo "Invalid JSON — blocking PR"
    exit 1
  }

Common questions

Q: What JSON parser is used? Python's json module for strict RFC 8259 compliance, plus json5 as a fallback when autoFix=true (handles comments, trailing commas, unquoted keys common in config files).

Q: Does it support JSON Schema Draft 2020-12? Yes — Draft-07, Draft 2019-09, and Draft 2020-12 are all supported via the jsonschema Python library.

Q: Can I validate newline-delimited JSON (NDJSON / JSON Lines)? Yes — set inputFormat: "ndjson" in the input. Each line is validated independently and aggregated results returned.

Q: Is it safe to send sensitive payloads? The actor runs on Apify's infrastructure. Inline payloads are processed in-memory per run, not persisted beyond the standard Apify dataset (which you can delete programmatically). For secret-sensitive workflows, prefer URL inputs with short-lived signed URLs rather than inline payloads.

Q: How does the autoFix feature work? It applies a sequence: (1) strip JS-style comments, (2) fix trailing commas, (3) quote unquoted keys, (4) convert single quotes to double. Each transformation is logged so you can audit what was changed.

Q: Cost per run? Apify compute-unit pricing. A 1,000-input run (URL-fetched + schema-checked) typically costs $0.02-$0.05.

Export integrations

• CSV / JSON / Excel / HTML (native Apify dataset download)
• Google Sheets (via Apify integration)
• Webhooks fired on invalid-JSON detection (great for Slack alerts)
• S3 / GCS direct sync
• Zapier / Make.com / n8n

Related scrapers

Source	Actor	Data
JSON Validator (this)	Syntax + schema	Data quality
Sitemap Scraper	URLs from sitemap.xml	Crawl surface
Robots.txt Analyzer	Crawl rules	Scrape compliance
Public APIs Directory	Free API catalog	API discovery
NPM Package	Package metadata	JS ecosystem

All free on Apify Store.

About the maintainer

Maintained by an active Apify developer (78 public actors covering scraping, MCP servers, data-validation tooling, and devops utilities). Technical articles on Hashnode, Telegraph, Write.as, and Mataroa covering JSON schema design, API-contract testing, and ETL data-quality patterns.

Need a custom data-validation pipeline (multi-schema validation, contract-testing harness, alert-on-drift)? Email spinov001@gmail.com or message t.me/scraping_ai.

Disclaimer

Designed for data-quality, API-testing, and development use. Respects URL-fetch rate limits and honors standard timeout behavior. Not affiliated with any specific JSON-Schema vendor or validator library.