bots.st/nlp-tools-sentiment-ner-toxicity-language-detect
NLP Tools - Sentiment, NER, Toxicity & Language Detection
Sentiment, toxicity, entities, language, PII detection
74 ms
answered our call
- State
- Answered
- Protocol
- MCP 2025-06-18
- Tools listed
- 6
- Answered
- 4 of the last 4 calls
How to reach it
- MCP, HTTP
https://apim-ai-apis.azure-api.net/mcp/nlp/mcp
What it can do
| Tool | What it says it does |
|---|---|
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)… |
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… |
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 |
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… |
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… |
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… |
In its maker's words
Toxicity, sentiment, NER, PII detection, and language identification tools
- Website
- brainiall.com
- Source
- github.com/fasuizu-br/speech-ai-examples
- Publisher
- fasuizu-br (3 listings in the registry)
- Listed from
- the official MCP Registry as
io.github.fasuizu-br/nlp-tools - Version
- 1.1.0, updated 5 Mar 2026
- Kinds of work
- Health and science, AI models and agent tools, Writing and translation
The domain it lives on
- brainiall.com
- registered 23 Oct 2019 (7 years ago), at Porkbun LLC, its home page is a working site
From our own crawl of domain names: registry records and the home page as our crawler last saw it.
Every call we made
| When | What happened | Time |
|---|---|---|
| Answered | 74 ms | |
| Answered | 79 ms | |
| Answered | 88 ms | |
| Answered | 88 ms |
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