AI news signals for investors and AI agents.
Get AI-analyzed financial news signals for you and your trading agent.
Signal engine
Clean inputs, ranked signals, usable data.
The product value is not another news feed. It is a cleaner data layer your AI agent can reason over without burning tokens on basic market-news cleanup.
How it works
From financial news to AI decisions
AI Analysis
Decision
Monitoring market-moving sources, filings, and corporate events, then turning them into structured news signals
Why use it
Spend your AI budget on decisions, not cleanup.
If you are building an AI trading bot or research agent, raw news is expensive context. StockNews.AI gives your workflow a cleaner starting point before your own agent starts reasoning.
Stop wasting LLM tokens on basic sentiment analysis
Your agent should not burn tokens summarizing every article or deciding whether a headline is bullish or bearish. Start with content summary, sentiment, importance, ticker tags, and source context already prepared.
Skip the messy news workflow
No scraping, deduping, source cleanup, ticker matching, or prompt chains just to understand what the article is about.
Give your agent market context, not raw noise
Each signal includes a reason, confidence, source trace, and price-at-event context so your bot can focus on filtering, strategy, and action.
Example agents
A few ways AI agents can use the feed.
Market pulse agent
Use SPY when your agent needs broad US market context before deciding which individual tickers deserve attention.
GET /api/news?symbol=SPY&limit=10Trading signal agent
Let your trading agent monitor a focused basket and only spend reasoning time on high-signal stories.
GET /api/news?symbol=NVDA,AMD,TSM&sentimentRating=verybullish,bullishBacktesting notebook
Capture the price at signal time, then compare later market prices inside your own database or notebook.
Store newsId + symbol + firstSeenAt + startPriceChatGPT MCP server
Paste the MCP URL into ChatGPT custom tools so your AI agent can call StockNews.AI tools directly.
https://stocknews.ai/mcp?api_key=sn_live_your_api_keyMCP access
Connect ChatGPT directly to StockNews.AI tools.
Choose No Auth in ChatGPT custom tools and paste your MCP server URL to start getting high quality stock news data.
https://stocknews.ai/mcp?api_key=sn_live_your_api_keyFAQ
Questions before connecting your AI agent.
The short version: start with the News Agent if you want to read signals, and use the API when your own AI agent needs the same structured data.
Who is StockNews.AI for?+
Stock investors can use the News Agent to understand market-moving news faster. AI agent users can feed structured news signals into their own agents, bots, dashboards, and research workflows.
Why use this instead of sending raw articles to my AI agent?+
Your agent should not waste tokens scraping, deduping, summarizing, tagging tickers, and doing basic sentiment analysis. StockNews.AI returns content summary, signal scores, reasoning, source URLs, and price-at-signal context first.
What AI model analyzes the news?+
StockNews.AI uses GPT-5.5 to analyze full article content, summarize what changed, score sentiment, and explain why the news may matter for a stock.
Can I trace the original news source?+
Yes. Signals include the original URL plus source context such as sourcesJson[].sourceUrl, published time, first seen time, and source count when available.
Does the API include price tracking?+
Signals can include startPrice when price data is available, so your AI agent or notebook can compare later market movement against the signal timestamp.
Is there a free tier?+
Yes. Free access is designed for testing and learning, with delayed data and smaller request limits. Paid plans are for live workflows and higher usage.
Can I connect StockNews.AI to ChatGPT with MCP?+
Yes. Use https://stocknews.ai/mcp?api_key=sn_live_your_api_key in ChatGPT custom tools. Choose No Auth, then paste the URL.
Access
Try the News Agent. Build with the API/MCP.
Stock investors can use News Agent to understand market-moving news. Trading agents can start with delayed samples, then scale with live API access, usage quotas, and event-filtered workflows.