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Metaverse Sentiment Auditor MCP
x402
Metaverse Sentiment Auditor MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.336716/call, status unknown (last checked 2026-10-13).
Analyzes a dataset to produce a sentiment audit summary for metaverse-related content or activity
Price / call$0.336716
Success—
StatusUnknown
How this service works
The premier global index of 1,069 monetized MCP nodes across 205 specialized subdomains. Gasless USDC runtime settlements via x402 V2 Spec on Base L2. Save 95% token context.
Output
Returns a JSON object with a 'summary' boolean field indicating the overall sentiment audit result for the provided dataset — true or false representing positive or negative sentiment determination.
Example use cases
Metaverse community health check
“I have a dataset of user interactions from our metaverse platform — can you run a sentiment audit on it and tell me if the overall tone is positive or negative?”
Brand sentiment monitoring in virtual worlds
“Audit the sentiment in this dataset of metaverse user reviews and conversations about our brand and give me a summary of whether it's trending positive or negative.”
Content moderation pre-screening
“Before we publish this batch of user-generated metaverse content, can you run it through the sentiment auditor to flag whether the overall sentiment is harmful or negative?”
Technical details
Endpoint
POSThttps://api.m2mcent.com/metaverse-sentiment-auditor-mcp-415/api/execute?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, paid, per-call sentiment audit specifically scoped to metaverse or virtual world content datasets and want a simple boolean summary output. It operates via the x402 micropayment protocol on Base L2 using USDC, making it suitable for automated agent workflows that settle payments programmatically.
Side effects
- Missing 'dataset' field returns validation error
- Empty or malformed dataset string may produce unreliable boolean output
- Payment failure via x402 protocol returns 402 status before execution
- Ambiguous or non-metaverse datasets may yield low-confidence boolean results
- Network timeout on large datasets
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| datasetrequired | string |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| summaryrequired | boolean |
Tags
x402
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