Public API & Model Deprecation Radar
Pricing
$3.00 / 1,000 extracted data record / events
Public API & Model Deprecation Radar
Monitor official deprecation notices and version sunsets for major public APIs, SDKs, and cloud services. Export deprecation radars to JSON & CSV. Zero proxies, fast run. Zapier ready. PPE ($0.003/record with 10 free preview items).
Pricing
$3.00 / 1,000 extracted data record / events
Rating
0.0
(0)
Developer
Deepak Sheoran
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
4 days ago
Last modified
Categories
Security
Limited permissionsShare
📋 Instant Sample Output (JSON Preview)
Fast, schema-compliant JSON format ready for automated pipelines (n8n, Make, Zapier, Clay):
[{"provider": "OpenAI","modelOrApi": "text-davinci-003","status": "DEPRECATED","sunsetDate": "2024-01-04","recommendedReplacement": "gpt-3.5-turbo-instruct"}]
⚡ Value Proposition: High-Agency Engineering vs Legacy Scrapers
Most data collection scrapers waste your budget by spinning up heavy headless browsers (Chrome/Puppeteer), demanding expensive $15/GB residential proxies, and crashing when layouts change.
Public API & Model Deprecation Radar is architected for production reliability:
- Zero Proxy Tax ($0.00): Executes via direct, hyper-optimized asynchronous HTTP/DNS connections in < 512MB RAM.
- Pay-Per-Event Predictability: You only pay for verified, delivered records ($0.003 / record).
- Zero-Charge-on-Error Guarantee: Upstream outages, empty deltas, or unresolvable targets emit diagnostic baseline records completely free ($0.00).
- Sub-5 Second Turnaround: Pure REST/HTTP pipelines deliver datasets in seconds rather than minutes.
🤖 AI Agent & Model Context Protocol (MCP) Integration
This Actor is packaged as an AI-first tool compatible with Claude Desktop, Cursor IDE, Windsurf, and LangChain / CrewAI agentic workflows.
Agent Trigger Rule:
"Use this tool when the user requests extract shutdown schedules, deprecation notices, and migration recommendations from major cloud ai & api vendor documentation. or needs structured JSON data for api-sdk-deprecation-radar without browser overhead or manual cleanup."
Claude Desktop / Cursor claude_desktop_config.json Snippet:
{"mcpServers": {"api-sdk-deprecation-radar": {"command": "npx","args": ["-y", "@apify/mcp-server-apify"],"env": {"APIFY_TOKEN": "YOUR_APIFY_API_TOKEN"}}}}
💰 Unit Economics & Cost Comparison
| Feature | Public API & Model Deprecation Radar | Traditional Puppeteer / Playwright Scraper |
|---|---|---|
| Residential Proxy Bandwidth | $0.00 (Zero Proxy Tax) | $12.00 – $25.00 / GB |
| Execution Memory Required | 256MB – 512MB RAM | 2048MB – 4096MB RAM |
| Pricing Model | $0.003 / record (Pay-Per-Event) | Monthly SaaS / Expensive Compute Runtime |
| Failure Billing Policy | Zero-Charge on Error ($0.00) | Billed for full runtime on crash |
| Execution Speed | 2–5 Seconds | 45–120 Seconds |
⚡ 1-Click Integration Blueprints
1. Sync Execution via cURL / REST API
Run the Actor synchronously and retrieve dataset records immediately in one HTTP call:
curl -X POST "https://api.apify.com/v2/acts/deepaksheoran172~api-sdk-deprecation-radar/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \-H "Content-Type: application/json" \-d '{}'
2. Python (apify-client)
from apify_client import ApifyClientclient = ApifyClient("YOUR_APIFY_TOKEN")run_input = {}# Start Actor run and wait for completionrun = client.actor("deepaksheoran172/api-sdk-deprecation-radar").call(run_input=run_input)# Fetch structured dataset recordsitems = client.dataset(run["defaultDatasetId"]).list_items().itemsfor record in items:print(record)
3. n8n / Make.com Webhook Automation
- Node Type: HTTP Request Node
- Method:
POST - URL:
https://api.apify.com/v2/acts/deepaksheoran172~api-sdk-deprecation-radar/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN - Headers:
Content-Type: application/json - Body: Raw JSON
{}
📥 Input Parameters
All properties feature built-in defaults; providing an empty object {} triggers a reliable default scan.
| Parameter | Type | Default | Description |
|---|---|---|---|
provider | string | openai | Configures API Provider for the extraction execution. Provide a valid input matching expected parameters or leave default to run automated scan. |
maxItems | integer | 10 | Maximum total records to extract and deliver to the output dataset during this run (for example 50 or 100 records) to govern compute time and data volume. |
📤 Output Dataset Specification
Output records strictly adhere to the official Apify dataset schema:
| Field Name | Type | Description |
|---|---|---|
modelOrEndpoint | string | Deprecated model or API endpoint |
shutdownDate | string | Official shutdown date |
recommendedReplacement | string | Recommended migration replacement |
status | string | Current lifecycle status |
❓ Frequently Asked Questions (FAQ)
Q: How does Pay-Per-Event (PPE) pricing protect my budget?
A: Unlike compute-time billing where you pay while waiting for slow responses, Pay-Per-Event charges only for legitimate data rows delivered. If an upstream service is down, the Actor pushes a diagnostic status record and does not bill you.
Q: Can I run this on a recurring schedule?
A: Yes! Use Apify's built-in Scheduler (Cron), or trigger it via Zapier, Make.com, or n8n on a daily, weekly, or hourly cadence.
Q: Are external proxies or browser engines required?
A: No. All requests use lightweight, high-performance asynchronous HTTP networking. There is zero proxy markup and zero browser overhead.
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