The missing layer between Claude and Wall Street

If you've used Claude for financial research, you've probably run into the same frustration. The reasoning is excellent: it can synthesize a messy situation, pull a thread across documents, explain something complicated clearly. But ask it about last quarter's earnings call, a filing from two weeks ago, or something that moved markets this morning, and it can't always help. Not because it can't reason about it, but because it doesn't have the data. That's just how language models work. Even with web search it just isn’t enough to fill the quality gap that institutional clients expect.

What Bigdata.com adds

Bigdata.com is now available as an MCP connector for Claude, which means you can link it directly inside Claude.ai through Settings → Connectors. Once connected, Claude can draw on:

• Over a billion financial documents: fundamentals, filings, earnings transcripts, premium news
• Real-time news feeds
• Structured, deterministic data from trusted sources for the essentials around fundamentals, earnings, pricing, etc.
• 20+ years of archive depth, purpose-built for financial search and retrieval
• Premium source attribution on every claim - named source, date, and URL
• Financial-domain NLP built on RavenPack's institutional infrastructure, rather than general-purpose embeddings

See it in practice

Does it actually make a difference?

We ran a controlled evaluation across 32 reports and 8 standardized financial research tasks, scored blind. The biggest gap showed up in grounding quality (how well claims are anchored to real, traceable sources) where Claude with Bigdata.com scored 82% versus 61% with standard web search. Every other metric also improved, though more modestly: factual accuracy, completeness, recency, and depth all moved in the right direction.

Who it's most useful for

The practical benefit is greatest for anyone who currently context-switches between Claude and financial data sources: research analysts pulling earnings transcripts, portfolio managers tracking guidance shifts, data teams who need every output to be auditable back to a primary source. The connector doesn't change how you use Claude; it just means you don't have to leave the conversation to verify or supplement what it's telling you.

Go further with Skills and Plugins

The connector gives Claude the data. Skills give it a playbook - structured templates for earnings previews, company briefs, risk assessments, and investment memos that produce consistent, institutional-quality output without prompt engineering. The skill is open source, so you can fork it and adapt the templates to your team's standards.

It also pairs with Claude Cowork for fully automated workflows. One example: a scheduled task that runs every morning, scans overnight news, cross-references your portfolio, and delivers individual PDF briefs with source attribution - all before you've had your coffee.

Getting started

Setup takes a few minutes:

If you have on active Bigdata account already go to the Bigdata MCP connector page and activate it with one click.