NLP Tools - Sentiment, NER, Toxicity & Language Detection
Toxicity, sentiment, NER, PII detection, and language identification tools
| Endpoint | https://apim-ai-apis.azure-api.net/mcp/nlp/mcp (streamable-http) |
|---|---|
| Registry version | 1.1.0 |
| Now | 6 tools · grade A (96) · pin ts_ec35dd2dc5d727a1c9622b8bd2b83edd · protocol 2025-06-18 |
| First / last listed | 2026-10-28 04:36 UTC / 2026-10-28 04:36 UTC |
| Grade over time | 2026-10-28: A (96), 6 tools |
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Tools: analyze_toxicity analyze_sentiment extract_entities detect_pii detect_language check_nlp_service
analyze_toxicity | Analyze text for toxic content.
Returns scores for 6 categories: toxic, severe_toxic, obscene, threat,
insult, identity_hate. Each score is 0.0-1.0.
BERT-based classifier with sub-15ms latency on GPU.
Args:
text: Text to analyze for toxicity (hate speech, insults, threats).
Returns:
dict with keys:
- toxic (float 0-1): Overall toxicity score
- severe_toxic (float 0-1): S params: text* |
analyze_sentiment | Analyze text sentiment.
Returns positive/negative classification with confidence scores.
DistilBERT-based with sub-10ms latency. Multiple domain-specific
model variants available.
Args:
text: Text to analyze for sentiment (positive/negative).
model: Model variant -- 'general' (default), 'financial', 'twitter'.
Returns:
dict with keys:
- label (str): 'positive' or 'negative'
params: text*, model |
extract_entities | Extract named entities (NER) from text.
Identifies persons, organizations, locations, and miscellaneous entities
with span offsets and confidence scores. BERT-NER based with sub-50ms latency.
Args:
text: Text to extract named entities from.
Returns:
dict with keys:
- entities (list): Detected entities, each containing:
- text (str): Entity text
- label (s params: text* |
detect_pii | Detect personally identifiable information (PII) in text.
Finds emails, phone numbers, SSNs, credit cards, IP addresses, and
person names. Optionally returns redacted text with PII replaced by
type labels (e.g. [EMAIL], [PHONE]). BERT-NER + regex ensemble.
Args:
text: Text to scan for personally identifiable information.
redact: If true, return redacted text with PII replaced by [TYPE].
params: text*, redact |
detect_language | Detect the language of text.
Supports 176 languages using fastText. Sub-1ms inference latency.
Returns ISO 639-1 codes with confidence scores.
Args:
text: Text to identify the language of.
top_k: Number of top language predictions to return (default: 3).
Returns:
dict with keys:
- language (str): Top predicted language ISO 639-1 code
- confidence (float 0-1): Confide params: text*, top_k |
check_nlp_service | Check health status of NLP API services and loaded models.
Returns:
dict with keys:
- status (str): 'healthy' or error state
- models (dict): Loaded model status per capability
- version (str): API version params: none |
Entries describe changes in tool definitions. They are not statements about a server, its quality or its author. The grade measures how the tool definitions fit model providers (token cost, schema compatibility, confusable names) as scored by the ToolFit engine at the time of the listing. JSON: append .json. Opt-out: how or hello@youraitools.co.