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Financial Datasets AI MCP

Financial Datasets AI MCP lets authorized agents query company fundamentals, financial statements and metrics, stock prices, SEC filings and filing sections, insider and institutional ownership, KPIs, news, macroeconomic data, index holdings, and stock-screening results.

Verdict

Financial Datasets AI MCP gives your team direct access to SEC filings, balance sheets, cash flow statements, and beneficial ownership data for any publicly traded US company. @mention it to pull quarterly earnings, extract risk factors from 10-Ks, or track activist investors without leaving your Project. Analysts, researchers, and anyone building investment memos get structured financial data in seconds instead of hunting through EDGAR. Auth requires OAuth2 with read scopes for company financials and filings. Note that data freshness depends on SEC filing schedules — expect a lag of hours to days after a company reports.

Common use cases

  • Pull quarterly earnings before investor calls
  • Extract risk factors from 10-K filings
  • Track activist investor stakes over time
  • Compare cash flow across peer companies
  • Build investment memos with live financials

Integration

Vendor
Financial Datasets AI MCP
Category
other
Auth
OAUTH2
Tools
28
Composio slug
financial_datasets_ai_mcp

Tools

  • Get balance sheet

    Retrieves a company's balance sheet, which provides a snapshot of its assets, liabilities, and shareholders' equity at a specific point in time. Essential for assessing a company's financial position.

  • Get beneficial owners

    Lists beneficial owners (holders of more than 5% of a company's shares, from SEC Schedules 13D/13G) with their filer CIK and reporting-person name. Optionally filter by case-insensitive name prefix. The response's `total` is the full match

  • Get beneficial ownership

    Retrieves beneficial-ownership stakes (holders of more than 5% of a class of shares) from SEC Schedules 13D and 13G. Schedule 13D stakes are ACTIVIST (intent to influence control: proxy fights, board seats, pushing for a sale); Schedule 13G

  • Get cash flow statement

    Provides a company's cash flow statement, showing how cash is generated and used across operating, investing, and financing activities. Key for understanding a company's liquidity and solvency.

  • Get company facts

    Get comprehensive company facts data for a stock ticker or CIK from Financial Datasets. Returns real-time information including market cap, number of employees, sector/industry classification, exchange listing, company location, website URL

  • Get earnings

    Retrieves earnings data from SEC filings. Returns a flat list of `EarningsRecord` entries — same shape in either mode. • COMPANY EARNINGS — pass a `ticker` to get the most recent SEC filings (8-K / 10-Q / 10-K / 20-F) for that company. Th

  • Get filing items

    Retrieves specific sections (items) from a company's SEC filings (10-K, 10-Q, or 8-K). Useful for extracting detailed information such as 'Business', 'Risk Factors', or 'Financial Statements and Supplementary Data'.

  • Get filings

    Get SEC filings data for a stock ticker or CIK. Returns a list of filings, including the accession number, filing type, report date, and URLs to the filing documents.

  • Get financial metrics

    Retrieves historical financial metrics for a company, such as P/E ratio, revenue per share, and enterprise value, over a specified period. Useful for trend analysis and historical performance evaluation.

  • Get financial metrics snapshot

    Fetches a snapshot of the most current financial metrics for a company, including key indicators like market capitalization, P/E ratio, and dividend yield. Useful for a quick overview of a company's financial health.

  • Get income statement

    Fetches a company's income statement, detailing its revenues, expenses, and net income over a reporting period. Useful for evaluating a company's profitability and operational efficiency.

  • Get index fund

    Get an ETF or index fund's holdings and each position's weight (percent of net assets) for a fund ticker (e.g. SPY), sourced from SEC fund-holdings filings. Returns the fund's latest filing by default, or the composition as of a past date.

  • Get insider ownership

    Retrieves insider ownership statements for a company: what officers, directors, and 10% owners actually HOLD (common shares, options, RSUs), sourced from SEC Form 3 (an insider's initial statement of ownership) and Form 5 (the annual statem

  • Get insider trades

    Retrieves insider trading transactions for a company, including purchases, sales, and other transactions by company officers, directors, and major shareholders. Useful for tracking insider sentiment and ownership changes.

  • Get institutional holdings

    Retrieves SEC 13F institutional holdings sourced directly from EDGAR. Query by filer_cik (what positions a filer holds) OR by ticker (which institutional filers hold this security) — exactly one is required. When no report_period filter is

  • Get institutional investors

    Lists institutional investors (SEC 13F filers) with their CIK and most recent reported name. Optionally filter by case-insensitive name prefix. Use this to discover the filer_cik to pass to get_institutional_holdings.

  • Get interest rates

    Retrieves the latest policy interest rates from major central banks (e.g., FED, ECB, BOE, BOJ). Returns a snapshot of each bank's current rate — no parameters required. Prefer get_macro_data with dataset='interest_rates', which also serves

  • Get kpi guidance

    Retrieves forward-looking KPI guidance items issued by company management in earnings releases and SEC filings. Filter by ticker, period (quarterly/annual), metric name, and date range.

  • Get kpi metrics

    Retrieves historical KPI taxonomy metrics extracted from SEC filings for a company (e.g., subscriber counts, ARPU, units sold). Filter by ticker, period (quarterly/annual), metric name, and date range.

  • Get kpi non gaap

    Retrieves non-GAAP KPIs reported by a company (e.g., Adjusted EBITDA, Free Cash Flow as defined by the company). Filter by ticker, period (quarterly/annual), metric name, and date range.

  • Get macro data

    Retrieves macroeconomic datasets. dataset='yield_curve' returns the daily US Treasury par yield curve: one object per business day with the keys date, 1_month, 1_5_month, 2_month, 3_month, 4_month, 6_month, 1_year, 2_year, 3_year, 5_year, 7

  • Get news

    Fetches recent news articles for a specific company or the broad market. Pass a ticker for company-specific news. Call with no arguments for the latest market-moving news, covering AI, macro, rates, earnings, geopolitics, war, energy, crypt

  • Get segmented financials

    Retrieves segment breakdowns from all three financial statement types (income statement, balance sheet, cash flow) in a single call. Returns revenue, operating income, and depreciation by product/segment; assets, goodwill, and long-lived as

  • Get stock price

    Fetches the most recent price snapshot for a specific stock, including the latest price, trading volume, and other open, high, low, and close price data.

  • Get stock prices

    Retrieves historical price data for a stock over a specified date range, including open, high, low, close prices, and volume.

  • List filing item types

    Provides a list of all available item names that can be extracted from 10-K, 10-Q, and 8-K reports, grouped by filing type.

  • List stock screener filters

    Retrieves all available filter fields and operators for the stock screener, grouped by category (income statement, balance sheet, cash flow statement, financial metrics, and company attributes like sector and industry). Use this to discover

  • Screen stocks

    Screens and filters stocks by financial metrics, valuation ratios, and company attributes. Combine multiple filter conditions to find stocks matching your investment criteria (e.g., revenue > $1B and P/E ratio < 20). Use list_stock_screener

Setup

Setup guide

  1. 11. In your Switchy workspace, open Settings and navigate to Integrations. 2. Find Financial Datasets AI MCP in the list and click Connect. 3. You'll be redirected to authorize Switchy to read company financials, SEC filings, and beneficial ownership records on your behalf. 4. Grant the requested scopes (typically read:financials and read:filings) and confirm. 5. Once redirected back to Switchy, you'll see a green checkmark next to the integration. 6. Open any Project and type '@Financial Datasets AI MCP get balance sheet for AAPL' to test the connection. 7. If the MCP returns Apple's latest balance sheet, you're ready to invoke any of the 28 tools by @mentioning the integration and describing what you need.

What teammates see: by default, memories from Financial Datasets AI MCP are scoped to the Project (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.

Works well with

Top models

Compatibility data appears once enough Projects have used this MCP together with a given model.

How Switchy teams use it

Not enough Projects yet to publish anonymised usage stats (we require ≥ 50 Projects per week).

Starter prompts

Quarterly Earnings Summary

@Financial Datasets AI MCP get the latest earnings data for TSLA and summarize the revenue, earnings per share, and any forward guidance mentioned.

Balance Sheet Snapshot

@Financial Datasets AI MCP retrieve the balance sheet for MSFT and calculate the debt-to-equity ratio and current ratio from the latest filing.

Risk Factor Extraction

@Financial Datasets AI MCP get the Risk Factors section from the latest 10-K filing for NVDA and list the top three risks mentioned.

Activist Investor Tracker

@Financial Datasets AI MCP show me all beneficial owners for GME with stakes over 5% and highlight any Schedule 13D filings that signal activist positions.

Cash Flow Trend Analysis

@Financial Datasets AI MCP get the cash flow statements for the last four quarters for AMZN and show me the trend in operating cash flow versus free cash flow.

Example outputs

Illustrative - representative of the model's voice and quality, not literal recordings.

Prompt

@Financial Datasets AI MCP pull the latest cash flow statement for AAPL and summarize whether operating cash flow is growing or declining year-over-year

Output

Retrieved Apple Inc.'s most recent cash flow statement from their 10-K filing. Operating cash flow for fiscal 2023 was $110.5B compared to $122.1B in 2022, representing a 9.5% decline. The decrease was primarily driven by changes in working capital, particularly accounts receivable and inventory timing. However, free cash flow remained strong at $99.6B after capital expenditures of $10.9B. Investing activities show continued share repurchases of $77.6B, and financing cash flow was negative $106.5B due to debt repayments and dividends.

Notes

This example demonstrates the MCP's ability to fetch structured financial statements and pair them with AI analysis. Note that data freshness depends on SEC filing schedules—annual 10-Ks arrive once per year, quarterly 10-Qs every three months. OAuth2 scope must include read access to financial data endpoints.

Prompt

@Financial Datasets AI MCP who are the beneficial owners holding more than 5% of TSLA stock, and has there been any activist filing activity in the last quarter?

Output

Current beneficial owners of Tesla (TSLA) with >5% stakes include: Vanguard Group (7.2%, passive Schedule 13G), BlackRock (6.1%, passive 13G), and Elon Musk (13.0%, Schedule 13D filed as CEO/Chairman). No new activist 13D filings detected in the past 90 days. Musk's most recent amendment was filed in April 2023 with no change in beneficial ownership percentage. All institutional holders filed passive 13G schedules, indicating no intent to influence control. Note that 13D/13G data reflects filings as of their submission date and may lag real-time ownership changes by up to 10 days per SEC rules.

Notes

This showcases the MCP's access to SEC ownership data and the AI's ability to distinguish between passive investors (13G) and activists (13D). Beneficial ownership filings have regulatory lag—investors have 10 days to file after crossing the 5% threshold. The MCP returns filer CIK and reporting-person names but cannot infer intent beyond what's disclosed in the filing type.

Prompt

@Financial Datasets AI MCP extract the 'Risk Factors' section from Microsoft's most recent 10-K and identify the top three risks related to AI or cloud infrastructure

Output

Retrieved Item 1A (Risk Factors) from Microsoft's fiscal 2024 10-K filing (accession number 0000891020-24-000123). The section contains 47 distinct risk disclosures totaling approximately 18,000 words. Top three AI/cloud-related risks identified: (1) Cybersecurity threats and operational failures in Azure cloud infrastructure could disrupt services and harm reputation; (2) Rapid AI technology evolution may render current investments obsolete or require significant additional capital expenditure; (3) Regulatory scrutiny over AI safety, data privacy, and antitrust concerns could limit product deployment or result in fines. Microsoft specifically highlights increased competition from other hyperscalers and the need to balance AI innovation speed with responsible deployment practices.

Notes

This example highlights the MCP's ability to pull specific filing sections (Items) and combine them with AI summarization. The 'Get filing items' tool returns raw text from SEC EDGAR, which can be lengthy—expect 5,000–20,000 words for Risk Factors in a large-cap 10-K. Rate limits may apply if querying multiple sections or companies in rapid succession. OAuth2 scope must include filing-item access.

Use-case deep-dives

Investor memo quarterly research

When this MCP replaces manual SEC filing pulls for small funds

A 3-person venture fund writing quarterly LP memos needs balance sheets, cash flow statements, and beneficial ownership data for 12-15 portfolio companies. This MCP wins here because it surfaces structured SEC data through 28 tools without opening EDGAR or parsing PDFs. The OAuth2 flow is a one-time setup, then the team can pull filings, earnings, and ownership stakes in seconds during memo prep. The trade-off: if you're only checking one or two companies per quarter, the auth overhead isn't worth it—just use the SEC site. But if you're tracking a portfolio or comp set and need repeatable queries across balance sheets, 13D/13G filings, and cash flow, this MCP cuts 20 minutes per company down to 30 seconds. Worth the integration for any team writing more than four investor updates a year.

M&A due diligence document review

How this MCP speeds early-stage target screening for corp dev teams

A corporate development team at a Series B SaaS company is screening five acquisition targets. They need to pull 10-Ks, extract Risk Factors and MD&A sections, and compare cash flow statements before deciding which two to pursue. This MCP handles the extraction—tools like Get filing items and Get cash flow statement return structured data instead of forcing analysts to download and parse PDFs. The 28-tool scope means you can also cross-check beneficial ownership and earnings in the same workflow. The boundary: if you're doing deep legal review or need non-SEC documents (cap tables, customer contracts), this MCP only covers the public-filing layer. But for the first pass—narrowing five targets to two based on financial health and disclosed risks—it's faster than manual EDGAR searches. Best fit for teams running more than three diligence processes a year.

Competitive intelligence weekly monitoring

When this MCP makes sense for tracking public competitor moves

A 6-person product team at a fintech startup monitors three public competitors. Every Monday, they check for new 8-K filings (earnings, leadership changes, material events) and compare quarterly cash flow trends. This MCP's Get filings and Get earnings tools automate the Monday ritual—no one has to remember to check EDGAR or set up email alerts. The OAuth2 setup takes 10 minutes once, then the team can query filings and company facts on demand. The catch: if your competitors are private or you need non-financial signals (product launches, pricing changes), this MCP won't help. It's purely SEC data. But if you're tracking public companies and want structured access to filings, balance sheets, and beneficial ownership without building your own scraper, this MCP is the right call for teams doing weekly or monthly competitive reviews.

Frequently asked

What does Financial Datasets AI MCP do in Switchy?

It pulls SEC filing data and financial statements directly into your AI workspace. You can query balance sheets, cash flow statements, beneficial ownership stakes, and specific filing sections without leaving Switchy. The MCP handles 28 different financial data operations, from earnings reports to company facts, so your team can analyze public company data in conversation threads instead of hunting through EDGAR.

Do I need special credentials to connect Financial Datasets AI MCP?

Yes, you'll authenticate via OAuth2 through Financial Datasets AI's service. You don't need SEC credentials yourself — the MCP acts as an intermediary. Whoever connects it in Switchy will authorize access on behalf of your workspace. Check with Financial Datasets AI about any account tier requirements or API rate limits before connecting.

Can it retrieve real-time stock prices or historical market data?

No. This MCP focuses on SEC filings and derived financial statements — balance sheets, cash flow, 10-K sections, beneficial ownership from 13D/13G forms. For live quotes or historical price charts, you'd need a separate market data service. Think of this as the regulatory filing layer, not the trading data layer.

How is this different from reading SEC filings on EDGAR directly?

EDGAR gives you raw HTML and XBRL documents. This MCP parses them into structured JSON you can query conversationally. Instead of downloading a 10-K and searching for Risk Factors, you ask the AI to summarize that section. It's faster for teams doing repeated financial analysis, but you lose the ability to see the original formatting and footnotes.

Who on the team should connect this MCP?

Whoever does financial research or investor relations work. Analysts, CFO staff, or anyone writing investment memos will get the most value. The person who connects it controls the OAuth token, so choose someone who'll stay on the team. Usage typically doesn't count against Switchy seat limits, but check your Financial Datasets AI plan for query caps.

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Data last verified 61 hours ago.Sources aggregated hourly to weekly. See docs/architecture/model-directory.md.