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Money Reactor Keyword Extractor
x402
Money Reactor Keyword Extractor is a paid API for AI agents from money-reactor.makar52nn2016.workers.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-11-02).
Extracts keywords and key phrases from any input text for tagging, SEO, and topic routing
Price / call$0.005
Success—
StatusUnknown
How this service works
Money Reactor paid API - catalog: https://money-reactor.makar52nn2016.workers.dev/.well-known/x402.json
Output
A JSON response containing extracted keywords and key phrases from the input text, suitable for use as content tags, SEO terms, or topic signals. The response includes a status field and an array or object of identified keywords/phrases ranked or grouped by relevance.
Example use cases
Auto-tagging blog posts for CMS
“Pull out the keywords and key phrases from this blog post so I can automatically populate the tags field in our CMS: 'Sustainable fashion brands are embracing recycled materials and circular economy principles to reduce textile waste.'”
SEO keyword discovery for landing page
“What are the main keywords in this landing page copy? I want to know what terms to target for SEO: 'Our cloud-based project management software helps remote teams collaborate in real time, track deadlines, and ship products faster.'”
Topic routing for content agent
“I have this user-submitted article and I need to route it to the right editorial category — extract the key phrases so I can figure out what topic bucket it belongs to: 'Central banks worldwide are raising interest rates to combat inflation, putting pressure on mortgage holders and slowing housing markets.'”
Technical details
Endpoint
GEThttps://money-reactor.makar52nn2016.workers.dev/api/keywords?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, cheap, per-call keyword extraction from arbitrary text without standing up your own NLP pipeline. At $0.005 USDC per call it is well-suited for high-volume content tagging, SEO enrichment, or topic routing in agent workflows. Prefer it over full LLM chat completions when you only need keyword/phrase output and want lower latency and cost.
Side effects
- Empty or missing text input returns an error or empty keyword list
- Very short text (single word or fragment) may yield poor or no keywords
- Non-English text may produce degraded keyword quality
- Rate limiting or payment failure (402) if USDC balance is insufficient
- Overly generic text may return only stopwords or low-value keywords
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"status": "ok"
}
}Tags
x402
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