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

IndexedMITRemote (HTTP)★ 3

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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/mcp Remote (HTTP)

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About

Toxicity, sentiment, NER, PII detection, and language identification tools

Reviews

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Permissions

What this server can do and what it asks for, from its tool list, install config and code. Checked Nov 1, 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_sentiment
analyze_toxicity
check_nlp_service
detect_language
detect_pii
extract_entities

Network hosts it talks to 4

api.brainiall.com · found in code
apim-ai-apis.azure-api.net · found in remote endpoint, install command, code
context7.com · found in code
pronunciation-assessment--fabiosuizu.run.tools · found in code

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-only
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' - score (float 0-1): Confidence score for the predicted label - scores (dict): All label scores (positive, negative)
analyze_toxicityAnalyze Toxicityread-only
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): 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-only
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_languageDetect Languageread-only
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): 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-only
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]. 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-only
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 (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 (3 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
Source: Official MCP Registry github-graphql

Rank

of 44,833 in Connectors

Score

0.588

Security 30%not yet
Popularity 25%0.46
Freshness 20%0.80
Rating 15%not yet
Docs 10%0.88

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Grades

Freshness

Active in the last 90 days. Last activity 3 months ago.

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Security

Security scan: in progress. Grades from our dependency, secret, code and prompt-injection checks appear here once they launch. Until then, check the code before you install.

Indexed

Found automatically from a public source. Not yet claimed by its publisher.

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Availability

100% uptime, last 30 days (1 check)

Last check: 6 days ago
Status: Up
Median response: 1.1 s

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NLP Tools - Sentiment, NER, Toxicity & Language Detection MCP server. Agent Mart. https://agentmart.dev/connectors/fasuizu-br-nlp-tools (last updated 2026-10-24)