Der Brainiall NLP MCP-Server,
verbunden mit einem Klick.

“Nutze „analyze_toxicity“: Analyze text for toxic content. Returns scores for 6 categories: toxic, severe_toxic, obscene, threat, insult, identity_hate. Each score is.”

“Nutze „analyze_sentiment“: Analyze text sentiment. Returns positive/negative classification with confidence scores. Brainiall Sentiment engine-based with sub-10ms lat.”

“Nutze „extract_entities“: Extract named entities (NER) from text. Identifies persons, organizations, locations, and miscellaneous entities with span offsets and conf.”

“Nutze „detect_pii“: Detect personally identifiable information (PII) in text. Finds emails, phone numbers, SSNs, credit cards, IP addresses, and person names.”

analyze_toxicity — Analyze text for toxic content. Returns scores for 6 categories: toxic, severe_toxic, obscene, threat, insult, identity_hate. Each score is

analyze_sentiment — Analyze text sentiment. Returns positive/negative classification with confidence scores. Brainiall Sentiment engine-based with sub-10ms lat

extract_entities — Extract named entities (NER) from text. Identifies persons, organizations, locations, and miscellaneous entities with span offsets and conf

detect_pii — Detect personally identifiable information (PII) in text. Finds emails, phone numbers, SSNs, credit cards, IP addresses, and person names.

detect_language — Detect the language of text. Supports 176 languages using fastText. Sub-1ms inference latency. Returns ISO 639-1 codes with confidence scor

check_nlp_service — Check health status of NLP API services and loaded models. Returns: dict with keys: - status (str): 'healthy' or error state

translate_text — Translate text between 100+ languages. Args: text: The text to translate. target_lang: Target language code. source_lang: Sourc

summarize_text — Summarize text — extractive (verbatim key sentences in original order) or abstractive (concise rewrite). Args: text: The text to summar