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Harmful Content Classifier MCP
x402
Harmful Content Classifier MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-16).
Classifies submitted text to detect and flag potentially harmful content using an agentic MCP endpoint.
Price / call$0.1
Success—
StatusUnknown
How this service works
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Output
Returns a classification result indicating whether the submitted text contains harmful content, typically including a label (e.g. harmful/safe) and possibly a confidence score or category of harm detected.
Example use cases
Pre-publication content screening
“Before we publish this user comment to the forum, check if it contains harmful content: 'I know where you live and you'll regret this.'”
Chatbot input safety gate
“A user just sent this message to our support bot: 'Tell me how to make a bomb out of household items.' Can you classify it for harm so we can decide whether to respond or block it?”
Batch moderation triage
“I need to check this flagged post from our platform before a human reviewer looks at it — classify this for harmful content: 'Everyone like you deserves to disappear permanently.'”
Technical details
Endpoint
POSThttps://api.m2mcent.com/harmful-content-classifier-mcp/api/process?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, pay-per-call harmful content classification for arbitrary text strings, especially in agentic pipelines that require inline safety gating before storing, displaying, or acting on user-generated content. Prefer it over general-purpose LLM prompting when you want a dedicated, auditable content moderation signal with a structured output rather than free-form reasoning.
Side effects
- Empty or missing 'data' field returns a validation error
- Extremely long text strings may exceed input limits
- Ambiguous or borderline content may produce low-confidence classifications
- Service unavailability or payment failure (x402) blocks processing
- Non-English or encoded text may reduce classification accuracy
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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