Retrieve reviews for your business or a competitor, including sentiment analysis and rating distribution.
MIT
594,794 tools. Updated 2026-09-21 00:21
"Exploring Sentiment Analysis with Google NLP" matching MCP tools:
- Retrieve and analyze management statements with sentiment and source attribution to assess company leadership communication.MIT
- Retrieve endpoints for social media analytics, sentiment analysis, influencer tracking, and trend detection across crypto, stocks, and NFTs. Analyze engagement metrics, track virality, and monitor real-time social sentiment with comprehensive indicators.MIT
- Extract NLP metrics from text for content auditing and classification: language detection, sentiment, topic extraction, entity recognition, readability. Accepts text directly, not URLs.MIT
- Obtain aggregated crypto market sentiment analysis including fear/greed, momentum, and funding bias. Pay $0.01 USDC via x402 micropayments.MIT
- Enqueue background NLP analysis for large documents to avoid blocking. Get readability, entities, and sentiment via a job ID for later polling.AGPL 3.0
Matching MCP Servers
- AlicenseAqualityBmaintenanceSentiment Analysis AI - MCP server providing AI-powered tools and automation by MEOK AI Labs49 npm47 PyPIMIT
- FlicenseNot gradedqualityCmaintenanceEnables end-to-end analysis of Reddit discussions: fetches posts, performs sentiment and toxicity detection, generates visualizations and word clouds, and optionally builds Neo4j knowledge graphs, all through natural language orchestration.-
Matching MCP Connectors
Sentiment, toxicity, entity extraction, PII, translation, summary, QA, fraud scoring, safety audit.
Toxicity, sentiment, NER, PII detection, and language identification tools
- Track sentiment changes over time across feedback sources to measure impact of releases, bug fixes, or feature launches with weekly or monthly analysis.MIT
- Analyze sentiment of NZX company announcements with AI-scored ratings from -1 to +1, including hedging analysis, buried risks, and key topics.MIT
- Finalize a journal entry and get AI analysis with sentiment, themes, and insights. Minimum 100 characters required.MIT
- Analyze retail investor sentiment from Reddit stock discussions across multiple subreddits. Get AI-powered sentiment analysis with confidence scores and key themes to gauge community opinion.MIT
- Analyze Reddit sentiment for any stock ticker by searching key subreddits. Returns bullish, bearish, and neutral counts along with sample posts to gauge market mood.MIT
- Retrieve historical Moltbook community digests with hourly sentiment analysis over a configurable 1-24 hour window. Track how sentiment, topics, and narratives evolve over time.MIT
- Combine recent news sentiment analysis with market impact assessment and sector context to evaluate news-driven price movements and make informed investment decisions.MIT
- Analyze Steam game reviews to extract sentiment, themes, and insights. Filter by topic, time, or sentiment for targeted analysis.MIT
- Get Odin's current Bitcoin market analysis with conviction level. Combines on-chain, macro, and sentiment data. Cached for 4 hours.MIT
- Retrieve sentiment analysis scores and labels (positive, neutral, negative) for customer conversations to evaluate overall sentiment direction.MIT
- Returns sentiment score and overall sentiment classification for input text, supporting up to 2000 characters.MIT
- Extract and summarize content from multiple URLs, including sentiment analysis and focused insights. Generate overall summaries for combined understanding.MIT
- Analyzes market sentiment by retrieving long-short ratios and comprehensive sentiment data for any trading symbol.MIT
- Analyze emotional tone in tweets matching a search query to gauge public sentiment on topics, with options for sample size and keyword frequency analysis.MIT
- Analyze sentiment of text with a confidence score. Pay 10 sats per call via Lightning.MIT