{"uid":"cap_7f3jEFqBqLFLqIcj0tW5L","slug":"x402-cloud-json-structurer-7e6b0aa8","name":"X402 Cloud JSON Structurer","description":"Agent-ready x402 APIs for AI video production, audio localization, web research, document extraction, data analysis, and structured JSON transformation.","url":"https://api.x402cloud.space/api/v1/json-structurer","method":"POST","headers":{},"bodySchema":{"type":"object","required":["input"],"properties":{"input":{"type":"object"},"options":{"type":"object"}}},"responseSchema":{"type":"object","required":["status","request_id","result"],"properties":{"usage":{"type":"object"},"result":{"type":"object","additionalProperties":true},"status":{"type":"string"},"payment":{"type":"object","additionalProperties":true},"warnings":{"type":"array","items":{"type":"string"}},"model_used":{"type":"string"},"request_id":{"type":"string"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_X5AwmarOANS8d3EG-DfiB","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Transforms arbitrary input objects into structured JSON output using AI-powered schema inference and data normalization","exampleAgentPrompt":"Take this messy JSON object with inconsistent field names and nested arrays and restructure it into a clean, normalized JSON format — here's the raw input: {customer_name: 'Jane Doe', 'order-id': 12345, items: [{qty:2, item:'widget'}]}.","exampleUseCases":[{"title":"Normalize e-commerce order payload","prompt":"I've got this raw order object coming from our legacy system with inconsistent field names and mixed types — can you restructure it into a clean normalized JSON with proper field names and consistent data types? Here's the object: {cust_nm: 'Acme Corp', ord_no: '9981', ttl: '199.99', itms: [{nm: 'Widget A', qty: '3'}]}."},{"title":"Structure scraped web data","prompt":"I scraped some product data from a website and it came back as a messy nested object — can you turn it into a clean, consistently structured JSON with fields like productName, price, description, and availability? Here's what I got: {prod: 'Blue Widget', $price: '$24.99', 'in-stock': 'yes', desc: 'A small blue widget'}."},{"title":"Reformat API response for database ingestion","prompt":"I'm getting back a weird JSON payload from a third-party API that I need to clean up before inserting into our database — can you restructure it into a flat JSON with snake_case field names? The input is: {UserID: 445, 'Full-Name': 'Bob Smith', emailAddr: 'bob@example.com', acct_status: 1}."}],"resultDescription":"Returns a JSON object containing a 'result' field with the AI-structured output, a 'status' string indicating success or failure, a 'request_id' for tracking, optionally 'model_used' indicating which AI model performed the transformation, 'usage' stats, 'payment' details, and any 'warnings' about the transformation.","failureModes":["Missing or empty 'input' field returns validation error","Malformed JSON in request body causes 400 error","Payment failure (insufficient USDC balance) blocks request processing","Ambiguous or empty input object may result in pass-through with warnings","Rate limiting may occur under high request volume","Model unavailability may cause 503 or timeout responses"],"whenToPreferThis":"Choose this endpoint when you need to normalize, reformat, or structure arbitrary JSON objects into a consistent schema using AI inference. It is ideal for cleaning up heterogeneous data from legacy systems, web scraping outputs, or third-party APIs before downstream processing. Prefer this over manual ETL scripts when the input schema varies unpredictably or when field names and types are inconsistent.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T18:46:36.470Z","isFirstParty":false}