NLP Tools - Sentiment, NER, Toxicity & Language Detection
Toxicity, sentiment, NER, PII detection, and language identification tools
Connector by fasuizu-br · GitHub account verified by the MCP Registry
Install
Works with Claude Code, VS Code, Cursor, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install connector/fasuizu-br-nlp-tools
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Remote endpoint
https://apim-ai-apis.azure-api.net/mcp/nlp/mcpRemote (HTTP)
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About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.
- Tools
- 6 read · 0 write · 0 deleteRead-only
- Secrets
- None asked for
- Install scripts
- Nothing to install (hosted)
- Runs as
- Hosted (remote endpoint)
Tools by what they do 6
From the running server's own tool list (tools/list) on Oct 25, 2026.
Read 6 · Look things up without changing anything.
analyze_sentimentanalyze_toxicitycheck_nlp_servicedetect_languagedetect_piiextract_entities
Network hosts it talks to 1
apim-ai-apis.azure-api.net· found in remote endpoint, install command
Tools (6)
As the server listed them on Oct 25, 2026. Descriptions are the server’s own words; hidden characters are shown as [U+…].
analyze_sentimentAnalyze 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' - score (float 0-1): Confidence score for the predicted label - scores (dict): All label scores (positive, negative)
analyze_toxicityAnalyze 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): Severe toxicity score - obscene (float 0-1): Obscenity score - threat (float 0-1): Threat score - insult (float 0-1): Insult score - identity_hate (float 0-1): Identity-…
check_nlp_serviceCheck 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
detect_languageDetect 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): Confidence for top prediction - predictions (list): Top-k predictions, each with: - language (str): ISO 639-1 code - confidence (float 0-1): Prediction confidence
detect_piiDetect 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]. Returns: dict with keys: - pii_found (list): Detected PII items, each containing: - text (str): The PII value found - type (str): PII type (EMAIL, PHONE, SSN, CRED…
extract_entitiesExtract 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 (str): Entity type (PER, ORG, LOC, MISC) - start (int): Character offset start - end (int): Character offset end - score (float 0-1): Confidence score - count…
Signals
- Stars
- 3
- Forks
- 0
- Open issues
- 24
- Last commit
- Aug 3, 2026 (2 months ago)
- Last release
- Jul 29, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Registry name
io.github.fasuizu-br/nlp-tools- Version
- 1.1.0
- Auth
- Auth not stated
- License
- MIT
- Repository
- github.com/fasuizu-br/speech-ai-examples
- Website
- brainiall.com
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
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Cite this page
NLP Tools - Sentiment, NER, Toxicity & Language Detection MCP server. Agent Mart. https://agentmart.dev/connectors/fasuizu-br-nlp-tools (last updated 2026-10-24)