Best Financial Data APIs for Model Context Protocol (MCP)

Twelve Data is a dynamic financial data platform catering to developers, analysts, and businesses looking for real-time financial data. Offering a wide array of information across stocks, commodities, forex, and cryptocurrencies, Twelve Data makes it easy to integrate market insights into various applications with its robust API. Users can access a rich set of features, including real-time price data, historical data, financial news, and advanced stock screening tools. With Twelve Data, businesses can leverage accurate and up-to-date information to make informed decisions, streamline trading strategies, and stay ahead of market trends. Its simple and accessible interface ensures that users can easily navigate the platform while powerful tools enhance their ability to analyze data effectively.

EODHD serves as a robust financial data API platform, granting developers and analysts seamless access to an extensive array of global market information through a single, cohesive interface. The platform boasts more than three decades of historical data and provides real-time and intraday feeds from over 60 stock exchanges, encompassing in excess of 150,000 tickers, which include stocks, ETFs, mutual funds, bonds, Forex pairs, and digital currencies. Users can benefit from a diverse selection of datasets, such as end-of-day prices, real-time OHLCV data, corporate actions including splits and dividends, financial news, technical indicators, macroeconomic statistics, and stock screening tools, all conveniently accessible through REST APIs and WebSocket connections. Additionally, EODHD facilitates the integration of this wealth of data into various applications, enhancing decision-making and analytical processes for its users.

CommodityPriceAPI is a developer-centric REST API that provides both real-time and historical pricing information for over 170 commodities, which encompasses precious metals like gold and silver, energy resources such as WTI and Brent crude, natural gas, and various agricultural products. The price data is compiled from exchange-grade sources and updated every second, supporting more than 150 different currencies for quoting. The API features five straightforward endpoints that streamline the entire process: it offers the latest rates, historical data dating back to January 1990, time-series analytics, fluctuation calculations, and a reference for symbols, all secured with a single API key and delivered in a clean JSON format. Users can expect to integrate the API in under five minutes without requiring any SDK. Additionally, the platform includes a dedicated MCP server, which allows AI assistants like Claude and Cursor to access both live and historical commodity data seamlessly. Designed for use in fintech dashboards, trading applications, agri-tech solutions, and energy monitoring systems, it boasts an impressive uptime of 99.97% and an average response time of less than 80 milliseconds, ensuring reliability and efficiency for all users. The versatility of the API makes it an essential tool for developers looking to incorporate commodity pricing into their applications.

SiftingIO serves as a comprehensive financial market data API designed for developers, fintech teams, analysts, and researchers who are creating applications that require market insights. It offers real-time quotes and continuous updates, alongside historical OHLCV data and reference datasets related to U.S. stocks, forex, cryptocurrencies, commodities, and on-chain markets via both REST and WebSocket interfaces. In addition, users can access a variety of datasets that include company fundamentals, financial statements, SEC filings, economic events, market operating hours, and technical indicators. To facilitate development and research, SiftingIO provides SDKs for Go, Python, and TypeScript, along with interactive API documentation, tools for Excel and Google Sheets, downloadable data exports, and an MCP server. A free tier is available for each market, featuring usage limits, while paid plans are structured based on market type and service tier. Users should note that the coverage and permissible usage may differ by market, plan, and data licensing agreements, ensuring a tailored experience for various projects. This flexibility makes SiftingIO an appealing choice for a wide range of financial data requirements.

SecFeed offers a comprehensive hosted API that allows users to search and integrate SEC EDGAR data into various applications, research processes, and AI-enhanced tools. This service includes features for searching filings, accessing extracted sections from 10-K and 10-Q reports, obtaining XBRL financial statements, and tracking insider transactions via Forms 3, 4, and 5. Furthermore, it provides insights into institutional holdings with Form 13F data, ownership disclosures, and event information from Form 8-K. The API delivers structured records that are directly linked to the original filings and supports real-time filing updates and webhooks for immediate data access. Developers can utilize RESTful endpoints along with Python and Node.js clients, as well as an OpenAPI specification and a hosted Model Context Protocol server for seamless integration with AI applications. In addition to these features, SecFeed also presents federal contracting opportunities and award data, enabling searches associated with public-company tickers. This platform is tailored for developers, quantitative researchers, fintech innovators, and AI developers who require programmatic access to filings and essential public-sector information, ensuring they have the tools needed for efficient data analysis and application development. With its robust offerings, SecFeed stands out as a vital resource in the realm of financial data accessibility.

Equibles is an advanced platform that harnesses AI technology to provide comprehensive US stock-market data tailored for both investors and developers. It offers a wide array of resources including full-text search for SEC filings, transcripts from earnings calls, details on 13F institutional holdings, insider trading information, congressional trades, short interest metrics, and squeeze scores, along with macroeconomic data from FRED, CFTC, and CBOE, as well as valuation multiples and an efficient stock screener. All of this information is made accessible through an AI research assistant named ALVIS, a hosted Model Context Protocol (MCP) server, and a public REST API that is meticulously documented using OpenAPI standards. Users can benefit from a free tier that allows up to 100 API calls per day without requiring a credit card, making it an attractive option for those looking to explore stock data. Additionally, the platform's ease of use and powerful tools empower users to make informed investment decisions.

Worthune serves as a comprehensive catalog of financial planning models that are accessible via a REST API, managed through an MCP server, and available in the form of embeddable calculators. Each model adheres to a versioned public specification and undergoes rigorous Concordance testing; this necessitates that an independent second implementation, crafted in a language distinct from the original specification, must align with the production engine across 250 specific cases per model, achieving an accuracy of one part in a billion prior to any release. Continuous integration processes ensure that every modification triggers the harness, where any discrepancies halt the release process. Furthermore, each response includes the specification version, the government constants utilized, their primary sources, and check dates, along with a SHA-256 decision record that can be stored and recomputed later to validate the origin of the figures presented. Designed with developers in mind, Worthune enhances financial mathematics for applications in fintech, wealthtech, and banking sectors; it is particularly valuable for teams needing to demonstrate compliance to reviewers concerning the origins of financial data, as well as for AI agents that require reliable and deterministic financial computations instead of mere predictive outputs. This unique approach not only fosters trust but also ensures precision and accountability in financial modeling.