The Best Stock Sentiment Data Providers in 2026: An Honest Comparison
We compared the major stock sentiment data providers and APIs on coverage, methodology, developer experience, and price. Including where each one beats us. A practical guide for traders and builders choosing a sentiment source in 2026.
If you need stock sentiment data in 2026, the short answer: LunarCrush is the strongest choice for crypto social sentiment, QuiverQuant owns congressional and alternative data, SentiSense (that's us) is the best value for model-scored, per-stock sentiment with an API built for AI agents, and if you only need raw fundamentals and prices, a commodity data API will serve you better than any sentiment provider.
That's the whole conclusion. The rest of this post is the evidence, including the places where our competitors are genuinely better than we are.
Full disclosure up front: SentiSense is our product. We build a sentiment API for a living, so we have opinions. We have tried to keep the comparison factual, we link to every provider, and we say clearly where each one wins. Pricing was verified against published pages in July 2026 and may change.
The comparison at a glance
| Provider | Sentiment methodology | Coverage | API | Entry price | Best for |
|---|---|---|---|---|---|
| SentiSense | Model-scored polarity + sentiment score, fine-tuned on financial text | US stocks + ETFs, news + social | REST, Python + Node SDKs, MCP | Free tier; PRO $15/mo, no monthly cap | Per-stock sentiment depth, AI agents |
| LunarCrush | Proprietary social scores (Galaxy Score, AltRank) | Crypto first, thin equities | REST, SDK, CLI, MCP | Free tier (market data only); full API $300/mo | Crypto social sentiment |
| StockGeist | Message counts + positive/negative classing | ~2,200 US tickers | REST + streams, credit-based | Dashboard $50/mo; API credits | Raw social mention volume |
| QuiverQuant | Mention counts, no model-scored polarity | US stocks, strong alt-data | REST, Python SDK, MCP | Web $15/mo; API from $30/mo | Congressional + alternative data |
| Perscient Pro | Editorial narrative tracking | Curated themes, not per-ticker | None | $2,950/yr | Narrative research for professionals |
| Commodity data APIs (FMP, Financial Datasets, etc.) | None, or thin add-ons | Broad market data | REST, some MCP | ~$20-200/mo | Fundamentals, prices, filings at scale |
Now the detail, one provider at a time.
What actually counts as sentiment data?
Before comparing vendors it's worth naming the split that matters most, because providers use the word "sentiment" for two very different things:
Mention counting tallies how often a ticker appears on Reddit, X, or in headlines. It's cheap to compute and genuinely useful for spotting attention spikes. But volume is not opinion: a stock getting mentioned 5,000 times because it's collapsing looks identical to one getting mentioned 5,000 times because it beat earnings.
Model-scored sentiment runs each message or article through a classifier trained on financial language and outputs a signed score. This is harder to do well. Generic LLMs score financial text inconsistently (we wrote about why prompt-engineering an LLM for sentiment fails and what fine-tuning on financial text changes), and sarcasm-heavy trader language breaks generic classifiers trained on product reviews.
Several providers in this comparison sell mention counting under a sentiment label. That's not a scam, it's a legitimately useful signal. But you should know which one you're buying, because they answer different questions: "is anyone talking about this stock" versus "what do they think about it."
LunarCrush: best for crypto social sentiment
LunarCrush has spent years building social-intelligence scores for crypto, and its Galaxy Score and AltRank are the closest thing that market has to standard social metrics. The developer experience is polished: REST API, CLI, SDK, and an official MCP server, with a real free tier.
Where it wins: if your universe is crypto, this is the category leader and it isn't close. The multi-platform social ingestion is broad and the scores are widely recognized.
Where it falls short: equities and price. Stock coverage is thin and social-only, with no fundamentals, filings, or analyst context around the signal. And the pricing has moved sharply upmarket: plans are sold as day passes ($5 to $45 per day), social data starts at $90/month, and full API access (the Builder tier) is $300/month, an order of magnitude above the entry price of most equity-focused options.
StockGeist: best for raw social mention volume on stocks
StockGeist is a sentiment dashboard and API from Neurotechnology, a long-established Lithuanian AI company. It tracks roughly 2,200 US tickers, ranks them by social message volume in near real time, and labels messages positive or negative, with a genuinely nice touch: classifying messages as "informative" versus "emotional."
Where it wins: the minute-by-minute mention-volume ranking is a clean way to watch attention rotate across tickers, and the credit-based API (10k free credits to start) is easy to trial.
Where it falls short: depth and momentum. The signal is primarily count-driven rather than deeply model-scored, fundamentals are explicitly a stub, there are no SDKs or agent integrations, and the published case studies demonstrating the signal's predictive value date from 2020. The dashboard tiers are also priced ambitiously for what they include: $50/month buys 7 days of history at 1-hour resolution, and $100/month buys 30 days at daily resolution.
QuiverQuant: best for congressional and alternative data
QuiverQuant owns a category: if you want to track what US politicians trade, this is the brand people name. Around that anchor it has built a broad alternative-data catalog (insider trading, lobbying, government contracts, WallStreetBets scraping) with a web app, Python SDK, and an MCP server with thoughtfully designed tools.
Where it wins: breadth of alternative datasets at a low price, and years of accumulated congressional-trading history with computed returns. The $15/month web tier is one of the best value products in retail finance.
Where it falls short: sentiment specifically. Its social data is mention counts and trend lines, not model-scored polarity. If sentiment is the signal you're actually buying, Quiver is the wrong tool aimed at the right neighborhood.
Perscient Pro: best for narrative research
Perscient Pro comes from the Epsilon Theory team and does something nobody else here does: it tracks how narratives form and spread through financial media, semantic framing rather than per-message polarity. It's editorial, opinionated, and respected.
Where it wins: professional investors who want to understand the story the market is telling itself, with a human analyst brand behind it.
Where it falls short: it's not data infrastructure. No API, no per-ticker real-time feed, and at $2,950/year it's priced for professionals, not builders.
Commodity data APIs: best when you don't actually need sentiment
Providers like Financial Modeling Prep and Financial Datasets sell broad, cheap, well-documented market data: prices, fundamentals, filings, estimates. Some bolt on basic social endpoints, but sentiment is not their product and they don't pretend otherwise.
Where they win: breadth and price-per-call on commodity data. Nobody in the sentiment category can or should compete with them on raw market-data volume.
Where they fall short: by design, they have no proprietary signal. Everyone gets the same SEC filings and the same prices. Whatever edge exists in commodity data is already in the price.
The practical pattern we see most often: builders pair a commodity data API for facts with a sentiment API for signal. They're complements, not substitutes.
SentiSense: best for model-scored stock sentiment and AI agents
SentiSense is us, so grade this section accordingly.
Our sentiment pipeline is built on models fine-tuned specifically on financial text from news and social sources, work that draws on 13 years of research experience in sentiment analysis, NLP, and machine learning. Every US stock and major ETF gets a continuously updated sentiment polarity, a composite SentiSense Score, mention volume, and social dominance, with entity-level tracking underneath so a headline about a CEO attributes to the right company. Around the sentiment core we serve fundamentals, analyst consensus, institutional holdings, congressional and insider activity, and per-segment KPIs, so the signal comes with context.
For builders: the API has Python and Node SDKs, an MCP connector so Claude, Cursor, and other agent tools can query it directly, and an agent skill that drops into agent frameworks without writing a client. The free tier is 1,000 requests/month. PRO is $15/month with no monthly request cap (300 requests/minute burst guard).
Where we fall short, honestly: we're US-focused, so if you need European or Asian equities we're not your provider yet. Crypto coverage doesn't approach LunarCrush's. And unlike Quiver, congressional data is a supporting dataset for us, not the flagship.
Where we win: if the thing you need is model-scored, per-stock sentiment with entity-level attribution, delivered through an API a human or an AI agent can build on in an afternoon, at $15/month, we believe that combination doesn't exist anywhere else on this list.
Which sentiment API is best for AI agents and trading bots?
As of mid-2026, four providers have shipped MCP servers: SentiSense, LunarCrush, QuiverQuant, and Financial Datasets. If your consumer is an AI agent rather than a human, that list is your starting point, because MCP is how agents discover and call tools without custom glue code.
Within that list the choice follows the data: LunarCrush for crypto agents, Quiver for alt-data agents, Financial Datasets for fundamentals-driven agents, and SentiSense for agents that reason about sentiment and market psychology. We'd add one practical note from our own dogfooding: agents burn through request quotas much faster than humans, which is why we removed our monthly cap entirely. Check the rate mechanics, not just the price, before wiring a provider into an agent loop.
What's the cheapest way to get stock sentiment data?
Free tiers, as of July 2026: SentiSense offers 1,000 API requests/month free, QuiverQuant has a functional free web tier, StockGeist starts you with 10,000 API credits, and LunarCrush's free Hobby tier covers market data only, with no social or sentiment metrics. For paid entry points on stock-focused sentiment specifically, SentiSense PRO at $15/month is the lowest-priced full-access tier in this comparison; the next comparable steps are Quiver's $30/month API tier (mention data rather than scored sentiment), StockGeist's $50/month dashboard tier, and LunarCrush's $90/month Individual plan.
How to choose
Three questions settle it:
- What universe? Crypto: LunarCrush. US equities: SentiSense, StockGeist, or Quiver.
- Volume or opinion? If attention spikes are enough, mention-count providers are cheaper to operate. If you need directional signal, you want model-scored sentiment.
- Human or agent? If an AI agent is the consumer, shortlist the MCP-equipped providers and read their rate-limit pages carefully.
And if you're skeptical of vendor comparisons written by vendors: good instinct. Every provider here has a free tier or trial. Pull the same ticker from two or three of them on a volatile news day and see which signal you'd actually trade on. That test costs nothing and settles more than any comparison table.
Want to run that test with us? Get a free SentiSense API key → and make your first call in under five minutes.