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Language Detector Filter MCP
x402
Language Detector Filter MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.06/call, status unknown (last checked 2026-10-16).
Detects the language of input text and filters or validates content based on language identification
Price / call$0.06
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 the detected language of the input text, likely including a language name, ISO language code, and possibly a confidence score indicating how certain the detection is. May also include filtering status indicating whether the content passes language-based criteria.
Example use cases
Multilingual chatbot input routing
“I have an incoming user message and I need to know what language it's in before routing it to the right localized support agent — can you detect the language of this text: 'Necesito ayuda con mi pedido, no llegó a tiempo'?”
Content moderation language gate
“Before I process this user-submitted post through my moderation pipeline, can you identify what language it's written in so I can apply the right rules? The text is: 'Dies ist ein Beispieltext von einem Nutzer.'”
Email language classification for CRM
“I'm sorting incoming customer emails by language so I can assign them to the right team — what language is this email body written in: 'Ciao, ho un problema con il mio abbonamento e vorrei parlare con qualcuno'?”
Technical details
Endpoint
POSThttps://api.m2mcent.com/language-detector-filter-mcp/api/process?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to programmatically identify the language of arbitrary text before routing, filtering, or processing it — especially in multilingual pipelines, customer support automation, or content moderation workflows where language-aware handling is required.
Side effects
- Empty or whitespace-only input may return an error or undefined language
- Very short text snippets may yield low-confidence or incorrect language detection
- Mixed-language content may return only the dominant language or an ambiguous result
- Non-textual input (numbers, symbols only) may fail to detect a language
- Rare or low-resource languages may not be recognized and may default to a fallback
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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