Materiality Watch

AI-powered website change monitoring that only alerts you on what actually matters.

Every change monitor floods you with noise. Footer edits, ad rotation, timestamp updates, hero image swaps. You set up monitoring to stay informed — instead you learn to ignore it.

Materiality Watch flips the model. You describe, in plain English, what kinds of changes you care about. Claude AI evaluates every diff against your criteria and suppresses everything else.

"Pricing changes, API deprecations, leadership changes. Ignore blog posts, copy polish, and navigation tweaks."

Same page. Same diff. Different verdict for different users.

---

Why this exists

There are 10+ website change monitors on the Apify Store. They all do the same thing: scrape a URL, diff it, summarize with generic AI. The category exists but is unwon — every competitor sits at 2-29 total users.

The gap: nobody lets the user define what "material" means.

	Generic monitors	Materiality Watch
Filter logic	"Is this significant?" (generic)	Your criteria in plain English
URLs per run	Usually 1	1-50 (portfolio mode)
Output	One alert per URL	One consolidated digest
History	Last snapshot only	Per-URL timeline (50 events)
Webhook	Per-URL fire	Single consolidated payload
False positives	High	Low (criteria-filtered)

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How it works

URLs + Criteria ──> Fetch ──> Diff ──> Claude AI Filter ──> Material changes only
                                              │
                                    "Does this match the
                                     user's criteria?"
                                              │
                                     ┌────────┴────────┐
                                     │                  │
                                   YES                 NO
                              ┌─────┴─────┐       (suppressed
                              │           │        silently)
                          Per-change   Consolidated
                           records      digest
                              │           │
                              └─────┬─────┘
                                    │
                              Webhook POST
                            (single fire/run)

On each scheduled run:

1. Fetch every URL concurrently, extract clean text via trafilatura
2. Diff against the last snapshot in Apify's key-value store
3. Classify with Claude Haiku — evaluate each diff against your criteria, score significance 1-5, tag categories
4. Suppress immaterial changes silently
5. Record material changes to the dataset with structured metadata
6. Digest — Claude writes a 3-6 sentence executive summary across all changes
7. Webhook — one consolidated POST per run (not one per URL)
8. Timeline — append to per-URL change history for audit trail

---

Use cases

Who	Watches	Criteria example
Founders	Competitor pricing pages	"Pricing changes, plan name or tier changes, new product launches"
DevRel	Upstream API docs	"API deprecations, breaking changes, new endpoints, schema changes"
Compliance	Regulatory bodies, T&C pages	"New requirements, enforcement actions, regulatory language changes"
Growth	Competitor landing pages	"Value prop changes, CTA changes, social proof updates"
Security	Vendor security pages	"New vulnerabilities, policy changes, incident disclosures"

---

Quick start

Input

{
  "urls": [
    "https://www.anthropic.com/pricing",
    "https://openai.com/api/pricing/"
  ],
  "criteria": "Pricing changes, model availability, rate limit changes. Ignore blog posts and footer changes.",
  "anthropic_api_key": "sk-ant-...",
  "emit_digest": true
}

Run locally

$apify run --purge

The first run establishes baselines (no alerts). Subsequent runs detect and classify changes.

Deploy

$apify push

Then schedule in the Apify Console — e.g., every 6 hours.

---

Output

Per material change

{
  "url": "https://example.com/pricing",
  "detected_at": "2026-05-07T14:00:00+00:00",
  "is_material": true,
  "significance": 4,
  "categories": ["pricing", "plan-name"],
  "summary": "The 'Pro' tier was renamed to 'Team' and price increased from $20 to $25/month.",
  "diff_excerpt": "-Pro Plan — $20/month\n+Team Plan — $25/month"
}

Consolidated digest

{
  "type": "digest",
  "n_changes": 3,
  "digest": "Anthropic raised Pro to $25 and renamed it to Team. OpenAI added a new tier. No changes to Mistral pricing."
}

---

Architecture

src/
├── main.py          # Actor logic — fetch, diff, classify, digest
├── __main__.py      # Entrypoint
└── __init__.py

.actor/
├── actor.json       # Apify actor configuration
├── input_schema.json
└── Dockerfile

Stack: Python 3.13 + Apify SDK + httpx + trafilatura + Claude API (Haiku)

Cost: ~$0.02/run + ~$0.001-0.003 per URL in Anthropic API costs. A portfolio of 20 URLs checked 4x/day runs about $5/month.

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Input reference

Field	Required	Default	Description
urls	Yes	—	URLs to monitor (1-50)
criteria	No	General materiality rules	Plain-English filter for what matters
anthropic_api_key	No	ANTHROPIC_API_KEY env var	Required for AI filtering
webhook_url	No	—	Consolidated POST on material changes
emit_digest	No	true	Generate executive digest per run
classify_model	No	claude-haiku-4-5-20251001	Model for diff classification
digest_model	No	claude-haiku-4-5-20251001	Model for digest generation

---

MCP Server (Agent Bridge)

This repo also includes an MCP server (src/index.ts) that wraps Apify actors as agent-friendly tools — including monitor_url which routes to this actor. See the build plan for details on the 7 high-level tools:

scrape_url · web_search · web_research · monitor_url · extract_structured · find_actor · run_actor

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Roadmap

• CSS selector / XPath restriction (diff only a region of the page)
• Image diffing for visual changes
• RSS feed ingestion alongside URLs
• Slack / Discord webhook formatting
• Named watchlists with persistent config

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License

MIT