A Financial News API for AI Agents and LLMs
A financial news API for AI agents and LLMs: real-time stories, deduplicated, tickers tagged, sentiment scored. Why scraping RSS is the expensive path, and what to use instead.
An AI agent or LLM app that reasons about stocks needs the news before it needs anything else. The default build is a scraper: a dozen RSS feeds, a crawler or two, and a dump of the last day's headlines into the model. That pipeline is the most expensive and most fragile part of the build. When every builder has an agent, the edge stops being the agent and becomes the data.
The short answer: instead of scraping RSS feeds, point your AI agent at a structured financial news API that returns real-time, deduplicated stories with the tickers already tagged and the sentiment already scored, then poll it for what is fresh.
Why scraping financial news is a tax, not an edge
A news scraper is a permanent maintenance commitment with three recurring costs.
Feeds break. Publishers change markup, RSS URLs go stale, rate limits tighten, and sources go silent without notice. The failure surfaces downstream, when the agent stops mentioning a name it should be covering.
Duplication compounds. The same story is republished by twenty outlets in an hour under twenty headlines. A raw scrape hands the model twenty near-identical items, and a single event reads as a wave. Deduplicating and clustering that coverage is continuous work, not a one-time job.
Entity resolution is the hardest layer. "The chipmaker's new accelerator" concerns NVDA only if the pipeline disambiguates it from every other chipmaker and separates the subject of a story from a passing mention. Resolving tickers over messy financial text is months of engineering, and a false tag pollutes everything downstream.
None of this is the differentiated part of the agent.
What a stock news sentiment API gives your AI agent
The alternative is a structured feed. Instead of raw headlines, the SentiSense news and stories API returns stories: clusters of related coverage, deduplicated so one event is one item. Each cluster is delivered as structured JSON, tagged with the tickers it concerns, scored for sentiment, timestamped when it broke, and ranked by significance. The feed maintenance, deduplication, and entity resolution are handled upstream.
Each document includes the canonical source URL. Clients that need the full article text retrieve it from the publisher directly via that link. For a side-by-side of the main feeds, see the sentiment data provider comparison.
Consuming the feed in real time
The feed is designed for subscription, not bulk export. Poll for fresh clusters on the tickers you follow, pull what is new since the last check, and wire it into the loop the agent already runs. An agent that reads each day's new stories, already clustered and scored, catches a shift the day it happens. A one-time dump goes stale within a day; freshness is the point of a real-time feed.
How to get a financial news API for your LLM: free key, SDKs, and MCP
The feed is a read-only API with a free tier. Python and Node SDKs are available, along with an MCP connector for calling the feed as a tool inside Claude, ChatGPT, or Cursor.
The scraper was never the edge. It was the tax.
Want to give your agent a real news feed? Get a free SentiSense API key → and make your first call in a few minutes. Prefer no code? The same feed connects to Claude or ChatGPT over MCP.