NLP Tools - Sentiment, NER, Toxicity & Language Detection
Toxicity, sentiment, NER, PII detection, and language identification tools
Connect it
Settings → Connectors → Add custom connector
URL: https://apim-ai-apis.azure-api.net/mcp/nlp/mcpSettings → Apps & Connectors → Advanced → Developer mode
Create connector with URL: https://apim-ai-apis.azure-api.net/mcp/nlp/mcp{
"mcpServers": {
"nlp-tools": {
"url": "https://apim-ai-apis.azure-api.net/mcp/nlp/mcp"
}
}
}claude mcp add --transport http nlp-tools https://apim-ai-apis.azure-api.net/mcp/nlp/mcp{
"servers": {
"nlp-tools": {
"type": "http",
"url": "https://apim-ai-apis.azure-api.net/mcp/nlp/mcp"
}
}
}6 tools, verified live
analyze_toxicityread-onlyAnalyze 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
analyze_sentimentread-onlyAnalyze 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'
extract_entitiesread-onlyExtract 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
detect_piiread-onlyDetect 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].
detect_languageread-onlyDetect 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
check_nlp_serviceread-onlyCheck 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
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