StockFit API

StockFit API is a financial data platform that gives developers, quants, and research platforms direct access to SEC filing data without the usual tradeoffs. Most financial APIs force you to choose between cheap tiers with accuracy issues or expensive enterprise contracts that drain a startup's budget. StockFit fills this gap by providing fundamentals, ownership data, ETF/MF exposure, insider transactions, and filings all pulled directly from SEC XBRL data with no derived middle layer. Every number is traceable back to the original filing, ensuring complete transparency and auditability for your models and analyses.

Built for real-world use cases, StockFit handles complex scenarios that other APIs ignore. Amended filings are properly processed and reconciled. Non-December fiscal years are computed correctly with accurate period mapping. Q4 financials are reconstructed from 10-K and 10-Q data, giving you complete annual views without gaps. The platform also includes rich economic models per company covering offerings, peers, operating levers, competitive advantages, flywheels, strategic initiatives, and failure modes. ETF and mutual fund exposure models cover mandate, portfolio construction, costs, sensitivities, and use cases making the data AI-friendly for LLM workflows.

With over 250 million facts and 5 million filings updated daily, StockFit provides the depth and freshness needed for serious financial analysis. The platform offers both a standard REST API and a native MCP server for integration with Claude, Cursor, and other AI tools. Whether you are building valuation models, running backtests, or powering a research platform, StockFit delivers standardized, model-ready financial data that you can actually build with.

Raw SEC XBRL Data with Full Traceability

Every financial fact in StockFit is pulled directly from SEC XBRL filings with no derived middle layer or synthetic data. Each number includes source references linking back to the original filing accession number and specific fact tags. This means you can always verify the data yourself, audit calculations, and trust that what you are modeling matches what companies actually reported. No more wondering if a third party transformed or rounded your data.

Intelligent Fiscal Period Handling

StockFit automatically handles the complexities that break most financial APIs. Amended filings are detected and reconciled so you always get the latest restated data. Companies with non-December fiscal years have their periods mapped correctly to standard calendar quarters. Q4 financials are intelligently reconstructed by comparing 10-K annual data against the sum of Q1 through Q3 from 10-Q filings. This gives you complete, accurate quarterly and annual data for any company regardless of their fiscal calendar.

Rich Economic and Exposure Models

Beyond raw financial statements, StockFit provides structured economic models per company. These models cover offerings, peer comparisons, operating levers, competitive advantages, flywheels, strategic initiatives, and failure modes. For ETF and mutual fund exposure, the platform includes mandate descriptions, portfolio construction details, cost structures, sensitivity analyses, and specific use case classifications. This structured data is designed to be AI-friendly and works naturally with LLM workflows for automated analysis and report generation.

Dual API Access: REST and MCP Server

StockFit offers two ways to access its data. The standard REST API provides full programmatic access to all endpoints for building applications, running scripts, and integrating with existing systems. Additionally, a native MCP (Model Context Protocol) server enables direct integration with AI tools like Claude and Cursor. This means you can query financial data conversationally within your AI assistant or development environment without writing custom API wrappers.

Automated Valuation and Financial Modeling

Analysts and quants can use StockFit to pull standardized financial statements directly into their valuation models. The traceable data ensures every input can be verified against original filings, which is critical for audit trails and regulatory compliance. With proper fiscal period handling and Q4 reconstruction, you can build DCF models, comparable company analyses, and LBO models that work across any company regardless of reporting structure. The economic models provide additional context on competitive advantages and operating levers to inform your assumptions.

Backtesting Quantitative Trading Strategies

Quantitative researchers can use StockFit to build and backtest factor-based trading strategies using raw fundamental data. The 250 million facts provide enough historical depth to test signals across multiple market cycles. Insider transaction data and ownership changes can be used to build event-driven strategies. The ETF/MF exposure models help understand how fund flows might impact individual stock prices. Since all data is traceable to SEC filings, your backtest results are based on the exact same information that was available to the market at each point in time.

Powering Financial Research Platforms

Research platforms and fintech applications can use StockFit as their primary data backend. The REST API makes it straightforward to build dashboards, screening tools, and alerting systems. The standardized financials eliminate the need to parse messy XBRL taxonomies yourself, saving months of development time. With daily updates, your users always have access to the latest filing data. The MCP server integration means you can also offer AI-powered research assistants that query financial data naturally.

LLM-Powered Investment Analysis Workflows

AI developers can leverage StockFit's MCP server to give large language models direct access to verified financial data. Instead of relying on a model's training data which may be outdated or inaccurate, you can query current financials, economic models, and exposure data in real time. This enables use cases like automated earnings report analysis, portfolio risk assessment, competitive landscape summaries, and investment memo generation. The structured economic models are specifically designed to work well with LLM reasoning capabilities.

StockFit offers a free tier that allows you to get started with a free API key and explore the platform's capabilities. For detailed pricing information on paid plans, visit the StockFit website pricing page. The platform is designed to be affordable for startups and independent developers while still providing the depth and accuracy needed by enterprise research platforms.

How does StockFit ensure data accuracy compared to other financial APIs?

StockFit pulls data directly from SEC XBRL filings with no derived middle layer or synthetic transformation. Every financial fact includes a source reference linking back to the original filing accession number and specific fact tags. This means you can always verify the data yourself against the official SEC documents. The platform also handles amended filings properly, ensuring you always get the latest restated data rather than stale or superseded information.

What companies and time periods does StockFit cover?

StockFit covers all US publicly traded companies that file with the SEC, including domestic issuers, foreign private issuers, and smaller reporting companies. The database contains over 250 million facts from more than 5 million filings. Coverage extends back to the adoption of XBRL reporting requirements, which varies by company but generally includes data from the early 2000s onward for larger filers. New filings are added daily as companies submit them to the SEC.

How does StockFit handle complex fiscal year scenarios?

StockFit automatically detects each company's fiscal year end and maps periods correctly. For companies with non-December fiscal years, all quarterly and annual periods are aligned to their actual fiscal calendar rather than being forced into calendar quarters. Q4 data is reconstructed by comparing annual 10-K figures against the sum of Q1 through Q3 from 10-Q filings. Amended filings are detected and the latest version is used. This ensures you always get accurate period-over-period comparisons.

Can I use StockFit with AI tools like Claude or Cursor?

Yes, StockFit provides a native MCP (Model Context Protocol) server that enables direct integration with AI tools that support this protocol, including Claude and Cursor. This allows you to query financial data conversationally within your AI assistant or development environment without writing custom API wrappers. You can ask natural language questions about financial statements, ownership data, or economic models and get structured responses backed by verified SEC data.