OpenAPI Contract & Breaking Change Monitor

Use this Actor to monitor openapi contract and breaking change changes and return decision-ready change signals. Compare OpenAPI specifications and identify removed paths, methods, parameters, responses, and required-field changes before clients break. Returns structured.

Quick start

Start with this working example and replace the target values with your own:

{
  "previousSpec": {
    "openapi": "3.0.0",
    "paths": {
      "/users": {
        "get": {
          "responses": {
            "200": {}
          }
        }
      }
    }
  },
  "currentSpec": {
    "openapi": "3.0.0",
    "paths": {
      "/users": {
        "get": {
          "responses": {
            "200": {}
          }
        }
      }
    }
  }
}

The Actor writes structured results to the default Apify Dataset and can be used from the Store, API, schedules, Tasks, automations and MCP-compatible AI workflows.

Input

• previousSpec — Previous OpenAPI specification: Previous OpenAPI JSON object.
• currentSpec — Current OpenAPI specification: Current OpenAPI JSON object.
• failRunOnIssue — Fail run on breaking change: Stop CI/release automation after report.
• previousSpecUrl — Previous OpenAPI URL: Optional public HTTP/HTTPS URL for an OpenAPI JSON or YAML specification.
• currentSpecUrl — Current OpenAPI URL: Optional public HTTP/HTTPS URL for an OpenAPI JSON or YAML specification.

All integration and advanced analysis fields are optional. The default example is intentionally runnable without configuring MCP or a previous-run baseline.

Output

The Dataset exposes predictable machine-readable output. Representative fields include results.

Pricing

This Actor uses Pay Per Event. The current factory base price is $0.004500 per result event. The Apify Store remains the source of truth for the price and plan/tier details shown to the buyer.

Use cases

• Run the buyer-ready workflows exposed as Apify Tasks without preparing a custom integration first.
• Use the Actor from API or schedules for recurring collection, comparison or monitoring.
• Feed the structured Dataset output into spreadsheets, databases, automations or AI agents.
• Compare repeat runs when the product supports snapshots or previous-run inputs.

Automation and AI

Use the same Actor through Apify API, schedules, public Tasks and the Apify MCP server. Outputs are structured for downstream workflows and AI agents rather than requiring manual copy/paste.

Limitations

• Public websites and upstream APIs can change markup, access rules, rate limits or field availability without notice.
• Fields that are not publicly available are returned as unavailable or omitted rather than fabricated.
• Analytical outputs depend on the quality and coverage of the supplied or collected source data.
• Treat marketplace, reputation, workforce, safety or commercial signals as decision support and validate material decisions against the underlying source evidence.

Decision-ready workflow (verified scope)

For: API engineering teams.

Outcome: Catch removal of operations and parameters, newly required parameters and mandatory request bodies.

Input: Previous and current OpenAPI spec objects or URLs; access public URLs only.

First-run honesty: Without an earlier snapshot, this Actor reports the current records. It does not claim that every listing or record is newly added, nor that a trend was measured. A meaningful change needs an actual previous snapshot.

Evidence and costs: The Actor analyzes data provided as JSON or an accessible Apify Dataset, except the OpenAPI monitor which can also read public spec URLs. It does not guarantee direct marketplace crawling or guaranteed revenue. Review the source records, run cost, and Apify Store pricing before recurring deployment.

Detailed documentation

Detailed documentation

Compare OpenAPI specifications and identify removed paths, methods, parameters, responses, and required-field changes before clients break.

Why use this Actor

API providers can ship contract changes that look small in source control but break SDKs, integrations, customers, and automated workflows. This Actor is designed for repeatable automation rather than a one-off demo. It produces structured, machine-readable evidence that can be scheduled, called through the API, saved as an Apify Task, or inserted into a larger Actor-to-Actor workflow. The goal is to make the result useful to both humans and automated agents without hiding the decision behind an opaque score.

Key features

• semantic OpenAPI path/method/parameter comparison.
• deterministic contract fingerprint.
• breaking versus non-breaking classification.
• optional fail-run for CI and release gates.
• Structured output designed for downstream automation and monitoring.
• Deterministic behavior suitable for regression tests and scheduled Tasks.
• No external paid AI service is required for the core result.

Input

Use the Actor input form or API. Dataset-oriented products accept inline test data and, where applicable, an Apify dataset selected through a READ-scoped resource picker. Monitor-oriented products accept a current state plus a previous baseline. The input schema documents every field so Apify AI and other agents can select and populate the Actor without guessing what a parameter means.

Output

The default dataset contains a structured report with explicit status fields, counts, fingerprints, changes, and issue codes appropriate to this product. Fingerprints are deterministic for the normalized input state, which makes them useful for recurring comparisons. The source data is not silently mutated. When a fail-run option is enabled, the Actor writes the diagnostic report first and then fails the run so an upstream scheduler or integration can stop downstream processing.

Example

Create a Task using the provided default input, replace the example values with your own dataset or baseline, run it once to establish evidence, and save the resulting fingerprint or report as the next comparison baseline. For scheduled workflows, run the same Task hourly, daily, or weekly according to how quickly the underlying data can change.

Use cases

• CRM ingestion workflows.
• RAG ingestion workflows.
• e-commerce catalog workflows.
• job feed workflows.
• lead enrichment workflows.
• real-estate feed workflows.
• analytics warehouse workflows.
• financial feed workflows.
• review aggregation workflows.
• social metrics workflows.

Pricing

The planned pricing is pay-per-event with one clear primary event for one completed structured report. The current planned event price is $0.00450. The design intentionally avoids artificial premium events. If future versions add an independently valuable enrichment or action, pricing will be reviewed against real usage and platform costs before any change.

Limitations

This Actor evaluates the configured input and does not promise semantic truth beyond observable data. Very large datasets are capped by the configured maximum-item limit. Nested object semantics are intentionally conservative unless the product explicitly reports them. Baselines supplied by the user remain the user's responsibility. A PASS means the configured rules passed, not that every possible business or compliance requirement has been satisfied.

Integration and automation

Use Apify Tasks for reusable presets and Schedules for recurring checks. Dataset-oriented variants are designed around least-privilege access so a selected dataset can be read without granting unrestricted access to unrelated storage. The structured output can be consumed by another Actor, webhook receiver, database loader, alerting layer, CI system, or AI agent.

Gen2 decision intelligence

This Actor preserves its original analysis and adds a decision layer with baseline awareness, regression detection, confidence, GO/WARN/BLOCK executive output, and an optional economic-impact estimate. Economic estimates are produced only when the user supplies valuePerImpactUnitUsd; the result states the calculation basis instead of inventing monetary value.

Agent execution and AI discovery (October 2026)

Use this Actor when: Compare OpenAPI specifications to detect removed paths, changed methods, parameters, responses and required fields. Identify potential breaking API changes and export structured contract findings before release.

For AI agents and automations:

• Find this Actor in Apify Store by its use case and verify its actual input and pricing through Apify MCP (search-actors and fetch-actor-details). Availability and ranking in Apify AI are controlled by Apify; discovery is not guaranteed.
• Read the Input tab or input schema. Recognized fields include previousSpec, currentSpec, failRunOnIssue, previousSpecUrl, currentSpecUrl, valuePerImpactUnitUsd, monthlyRuns, previousAnalysis. Required fields: See the Input tab for valid example values. Do not invent records or credentials.
• Supply a small representative input first. Use Apify API, Tasks, or MCP to run and retrieve the structured dataset; inspect the output schema rather than assuming all inputs produce the same rows.
• For programmatic calls, set timeouts and maxTotalChargeUsd in run options to limit exposure. Check the Apify Pricing tab for billable events and discounts.
• Payment compatibility: this Actor is published with limited permissions and pay-per-event pricing. Apify AGI prepaid x402 tokens can execute limited-permission Actors. Direct per-request payment is a separate, conditional feature that may require additional eligibility checks and creator verification. Do not interpret this paragraph as proof of approved KYC or guaranteed payment acceptance.
• This Actor does not independently guarantee real-time access to a third-party source. Verify input provenance and important conclusions, and do not supply confidential personal data unnecessarily.