Queue a background NLP analysis of a document for readability, entities, and sentiment, returning a job ID immediately. Use for large documents to avoid blocking; poll progress with get_job_status.
AGPL 3.0
304,944 tools. Last updated 2026-07-22 11:44
"Exploring Sentiment Analysis with Google NLP" matching MCP tools:
- Fetch SEC EDGAR earnings filings, compute FinBERT sentiment, extract key themes, detect tone shifts, and output a catalyst score with actionable signals.MIT
- Retrieve reviews for your business or a competitor, including sentiment analysis and rating distribution.MIT
- 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
- Track sentiment changes over time across feedback sources to measure impact of releases, bug fixes, or feature launches with weekly or monthly analysis.MIT
Matching MCP Servers
- AlicenseAqualityAmaintenanceSentiment Analysis AI - MCP server providing AI-powered tools and automation by MEOK AI LabsLast updated42MIT
- AlicenseBqualityAmaintenanceNLP without the bloat — 45 tools for sentiment, keywords, readability, summarization. Zero heavy dependencies. 42KB wheel.Last updated451MIT
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- Analyze sentiment of NZX company announcements with AI-scored ratings from -1 to +1, including hedging analysis, buried risks, and key topics.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
- Retrieve sentiment analysis scores and labels (positive, neutral, negative) for customer conversations to evaluate overall sentiment direction.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
- Combine recent news sentiment analysis with market impact assessment and sector context to evaluate news-driven price movements and make informed investment decisions.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
- 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
- Fetch company and market news with sentiment analysis. Export large datasets to JSON for financial analysis.MIT
- Combines TradingView technical analysis with Reddit sentiment and financial news for a comprehensive multi-source analysis of any asset.MIT
- Fetch user reviews for any iOS or Android app. Filter by star rating range and sort by recent or helpful for sentiment analysis and competitive research.MIT
- Perform advanced Google searches to retrieve AI Overview, organic results, and related searches for off-Amazon market research and demand analysis.MIT
- Submit an ad-hoc profiling job for a catalog table to compute column statistics, data dictionary, and data-quality metrics. Optionally enable NLP analysis for semantic enrichment.Apache 2.0