# S\&P 500 & Nasdaq-100 Free Cash Flow BI Analyzer (MCP & API) (`chlorella2026/sp500-ndx100-fcf-mcp`) Actor Institutional-grade Free Cash Flow (FCF), SBC-Adjusted True FCF, FCF Margin, and Peer Comparison MCP & API powered by official SEC EDGAR 10-K filings. - **URL**: https://apify.com/chlorella2026/sp500-ndx100-fcf-mcp.md - **Developed by:** [Jeff Wang](https://apify.com/chlorella2026) (community) - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## 📊 S\&P 500 & Nasdaq-100 Free Cash Flow BI Analyzer (MCP & API) Give your LLM agents, financial research workflows, and investment pipelines **verified, context-ready cash flow intelligence** directly from official **SEC EDGAR 10-K / 20-F XBRL** filings. In one call, retrieve 5-year historical **Operating Cash Flow (OCF)**, **CapEx**, **Headline Free Cash Flow (FCF)**, **SBC-Adjusted True FCF**, **FCF Margin %**, **FCF Conversion Rate**, and automated **Business Intelligence (BI) diagnostic flags**. Designed specifically for AI agents (via **Model Context Protocol - MCP**) and quantitative/financial applications (via **REST API**), this Actor eliminates LLM arithmetic hallucinations and context-window bloat by returning pre-cleaned, pre-aggregated institutional BI metrics instead of raw multi-megabyte SEC filings. *** ### Main features - ⚡ **Sub-10ms response times** for **516 pre-cached S\&P 500 & Nasdaq-100 (QQQ)** constituents backed by an embedded `1.08 MB` SQLite analytical engine. - 🔄 **Hybrid Read-Through Lazy Cache**: Instant local lookup for S\&P 500 / Nasdaq-100 giants, with automatic on-the-fly SEC EDGAR XBRL extraction and 7-day caching for **5,000+ other US public equities**. - 💎 **SBC-Adjusted "True FCF"**: Automatically deducts **Stock-Based Compensation (SBC)** from Headline FCF (`OCF - CapEx - SBC`) to expose real cash generation after employee equity dilution. - 🧠 **Automated BIE Diagnostic Flags**: Built-in Business Intelligence rules automatically flag **High SBC Dilution** (`>25%` of FCF), **Aggressive CapEx Expansion** (`>+35%` YoY AI/infrastructure buildout), and **Working Capital / Earnings Quality Drag**. - 🏷️ **Index Membership & Period Metadata**: Every record is tagged with `is_sp500` (`bool`), `is_qqq_100` (`bool`), `fiscal_year` (`int`), and `quarter` (`enum: 1, 2, 3, 4`). - 🔍 **Cross-Company Cash Cow Screener & Peer Benchmarking**: Screen all 516 index constituents by minimum FCF margin or rank peers side-by-side in milliseconds. - 🔌 **Native MCP & REST API Support**: Run as a local `stdio` MCP server (Claude Desktop, Cursor, Windsurf), an HTTP Standby API server, or a standard Apify Actor. - 🛡️ **100% Official SEC EDGAR Data**: Zero third-party API keys required and zero anti-scraping risk. Contains both `us-gaap` and `ifrs-full` XBRL taxonomy parsers. *** ### Example #### 1. Single Company 5-Year Deep Dive (`get_company_fcf_analysis`) For a ticker query like `ARM` or `NVDA`, the Actor returns a structured BI summary along with a 5-year annual historical series: ```json { "ticker": "ARM", "company_name": "Arm Holdings plc", "sector": "Information Technology", "is_sp500": false, "is_qqq_100": true, "latest_fiscal_year": 2026, "quarter": 1, "headline_fcf_millions": 979.0, "sbc_adjusted_true_fcf_millions": -73.0, "fcf_margin_pct": 19.9, "true_fcf_margin_pct": -1.48, "fcf_conversion_pct": 108.3, "fcf_yoy_growth_pct": 450.0, "bie_diagnostic_flags": [ "High SBC Dilution: Stock-Based Comp consumes 107.5% of headline FCF.", "Aggressive CapEx Expansion: CapEx jumped +148.9% YoY (e.g., AI/Infra buildout)." ], "historical_5yr_annual": [ { "ticker": "ARM", "cik": "0001973239", "company_name": "Arm Holdings plc", "sector": "Information Technology", "is_sp500": false, "is_qqq_100": true, "fiscal_year": 2026, "quarter": 1, "period_end": "2026-03-31", "ocf_millions": 1524.0, "capex_millions": 545.0, "fcf_millions": 979.0, "sbc_millions": 1052.0, "true_fcf_millions": -73.0, "revenue_millions": 4920.0, "net_income_millions": 904.0, "fcf_margin_pct": 19.9, "true_fcf_margin_pct": -1.48, "fcf_conversion_pct": 108.3, "fcf_yoy_growth_pct": 450.0, "updated_at": 1792988675 } ] } ``` #### 2. Side-by-Side Peer Comparison (`compare_peers_fcf`) Compare multiple competitors or index heavyweights (`["NVDA", "MSFT", "AAPL", "AMZN", "META", "GOOGL"]`) in a single call: ```json { "peer_comparison": [ { "ticker": "NVDA", "company_name": "NVIDIA CORP", "is_sp500": true, "is_qqq_100": true, "fy": 2026, "quarter": 1, "headline_fcf_M": 96676.0, "sbc_adj_true_fcf_M": 90290.0, "fcf_margin_pct": 44.77, "true_fcf_margin_pct": 41.81, "fcf_yoy_growth_pct": 58.87, "flags": [ "Aggressive CapEx Expansion: CapEx jumped +86.7% YoY (e.g., AI/Infra buildout)." ] }, { "ticker": "AMZN", "company_name": "AMAZON COM INC", "is_sp500": true, "is_qqq_100": true, "fy": 2025, "quarter": 4, "headline_fcf_M": 7695.0, "sbc_adj_true_fcf_M": -11772.0, "fcf_margin_pct": 1.07, "true_fcf_margin_pct": -1.64, "fcf_yoy_growth_pct": -76.6, "flags": [ "High SBC Dilution: Stock-Based Comp consumes 253.0% of headline FCF.", "Working Capital / CapEx Drag: FCF is only 9.91% of Net Income.", "Aggressive CapEx Expansion: CapEx jumped +58.8% YoY (e.g., AI/Infra buildout)." ] } ] } ``` #### 3. Dataset Ticker Directory (`list`) Retrieve all cached S\&P 500 and Nasdaq-100 constituents and their index membership flags: ```json { "total_count": 516, "tickers": [ { "ticker": "AAPL", "company_name": "Apple Inc.", "sector": "Information Technology", "is_sp500": true, "is_qqq_100": true, "fiscal_year": 2025, "quarter": 3, "period_end": "2025-09-27" }, { "ticker": "ARM", "company_name": "Arm Holdings plc", "sector": "Information Technology", "is_sp500": false, "is_qqq_100": true, "fiscal_year": 2026, "quarter": 1, "period_end": "2026-03-31" } ] } ``` *** ### ⚙️ Usage The S\&P 500 & Nasdaq-100 FCF Analyzer can be used in three ways: **as a native MCP server**, in **HTTP Standby / REST API mode**, or **as a standard Apify Actor**. #### 1. Normal Actor run You can run the Actor via the Apify API, schedules, integrations, or manually in the Apify Console by passing an input JSON object: ```json { "action": "get_company_fcf_analysis", "ticker": "NVDA" } ``` Supported `action` values: - `get_company_fcf_analysis`: Returns 5-year FCF metrics and diagnostic flags for `ticker`. - `compare_peers_fcf`: Side-by-side comparison for an array of `tickers`. - `screen_sp500_cash_cows`: Screens the 516 cached index constituents by `min_fcf_margin_pct`, `sector`, and `sort_by`. - `list`: Lists all tickers in the dataset with `is_sp500`, `is_qqq_100`, `fiscal_year`, and `quarter`. #### 2. Standby web server / HTTP REST API When running in [**Standby mode**](https://docs.apify.com/actors/running/standby), you can query clean REST endpoints directly via `GET` requests for sub-second responses: ```bash ## Single company 5-year FCF analysis curl "https://chlorella2026--sp500-ndx100-fcf-mcp.apify.actor/api/fcf?token=&ticker=NVDA" ## Multi-company peer comparison curl "https://chlorella2026--sp500-ndx100-fcf-mcp.apify.actor/api/compare?token=&tickers=NVDA,MSFT,AAPL,AMZN,META,GOOGL" ## Cash cow screener (FCF Margin >= 25%, ranked by SBC-adjusted True FCF) curl "https://chlorella2026--sp500-ndx100-fcf-mcp.apify.actor/api/screen?token=&min_fcf_margin_pct=25&sort_by=true_fcf_millions" ## List all cached S&P 500 & Nasdaq-100 tickers curl "https://chlorella2026--sp500-ndx100-fcf-mcp.apify.actor/api/list?token=" ``` ##### Query parameters | Endpoint | Parameter | Type | Default | Description | |---|---|---|---|---| | `/api/fcf` | `ticker` | `string` | `"NVDA"` | Stock ticker symbol (e.g., `AAPL`, `MSFT`, `COST`). | | `/api/compare` | `tickers` | `string` | `"NVDA,MSFT,AAPL"` | Comma-separated list of stock tickers. | | `/api/screen` | `min_fcf_margin_pct` | `number` | `15.0` | Minimum Headline FCF Margin % filter. | | `/api/screen` | `sort_by` | `string` | `"true_fcf_millions"` | Sort column (`true_fcf_millions`, `fcf_millions`, `fcf_margin_pct`, `true_fcf_margin_pct`, `fcf_yoy_growth_pct`). | | `/api/list` | `cached_only` | `boolean` | `true` | Return cached dataset tickers (`true`) or full index universe (`false`). | | `/api/list` | `sp500_only` | `boolean` | `false` | Filter to S\&P 500 constituents only. | | `/api/list` | `qqq100_only` | `boolean` | `false` | Filter to Nasdaq-100 (`QQQ`) constituents only. | *** ### 🔌 Integration with LLMs (MCP) This Actor is designed for seamless integration with LLM applications, Claude Desktop, Cursor, Windsurf, OpenAI Assistants, and custom RAG/Agent pipelines via the [Apify MCP Server](https://blog.apify.com/how-to-use-mcp/). #### Connect via Apify MCP Server (Claude Desktop / Cursor) Add the following configuration to your `claude_desktop_config.json` or `.cursor/mcp.json` using your `APIFY_API_TOKEN`: ```json { "mcpServers": { "apify-sp500-fcf": { "command": "npx", "args": [ "-y", "@apify/actors-mcp-server", "--actors", "chlorella2026/sp500-ndx100-fcf-mcp" ], "env": { "APIFY_TOKEN": "" } } } } ``` Once connected, your AI assistant can invoke 4 core BI capabilities: 1. `list` — Discover all 516 S\&P 500 and Nasdaq-100 tickers in the dataset along with `is_sp500` and `is_qqq_100` flags. 2. `get_company_fcf_analysis` — Retrieve 5-year cash flow metrics and BIE diagnostic flags for a company. 3. `compare_peers_fcf` — Run side-by-side peer cash flow benchmarking. 4. `screen_sp500_cash_cows` — Screen the index for high-margin cash generators. *** ### 📐 BI Methodology & Metrics Definition Generic financial scrapers only report raw accounting numbers. This engine applies institutional Business Intelligence transformations to surface true cash profitability: | Field | Formula / Source | Why it matters for LLMs & Analysts | |---|---|---| | `ocf_millions` | SEC 10-K/20-F Operating Cash Flow | Cash generated from core business operations (`$ Millions`). | | `capex_millions` | Payments to Acquire PP\&E / Productive Assets | Capital expenditures required to maintain and grow infrastructure (`$ Millions`). | | `fcf_millions` | `OCF - CapEx` | Standard Headline Free Cash Flow (`$ Millions`). | | `sbc_millions` | Share-Based Compensation Expense | Non-cash employee equity compensation (`$ Millions`). | | `true_fcf_millions` | `FCF - SBC` | **SBC-Adjusted True FCF**: Treats recurring employee stock grants as a real economic cash cost. | | `fcf_margin_pct` | `(FCF / Revenue) * 100` | Percentage of every revenue dollar converted into Headline FCF. | | `true_fcf_margin_pct` | `(True FCF / Revenue) * 100` | Percentage of revenue converted into FCF after deducting SBC dilution. | | `fcf_conversion_pct` | `(FCF / Net Income) * 100` | Earnings quality indicator (`>100%` signals strong cash backing of GAAP earnings). | | `quarter` | `enum(1, 2, 3, 4)` | Calendar quarter corresponding to the fiscal year-end period (`period_end`). | *** ### ⏳ Performance optimization & Architecture ``` [ AI Agent / API Client Request ] │ ┌──────────┴──────────┐ (S&P 500 / QQQ 100) (Other US Tickers) │ │ Local SQLite Engine SEC EDGAR XBRL API (Lazy Mode) (516 companies, 1MB) │ │ Parse 10-K + Compute BI Ratios ▼ │ < 5 ms Response Write-Through to SQLite Cache (7-Day TTL) ``` #### Benchmark | Query Type | Data Source | Average Latency | Compute Memory | |---|---|---|---| | `list` (516 companies) | Embedded SQLite (`sp500_fcf.db`) | `~4 ms` | `128 MB` | | `screen_sp500_cash_cows` | Embedded SQLite (`sp500_fcf.db`) | `~6 ms` | `128 MB` | | `get_company_fcf_analysis` (Cached S\&P 500 / QQQ) | Embedded SQLite (`sp500_fcf.db`) | `~3 ms` | `128 MB` | | `get_company_fcf_analysis` (Uncached Small-Cap) | Live SEC EDGAR API + Write Cache | `~450 ms` | `256 MB` | *** ### 💰 Pricing When deployed on Apify Store using **Pay-Per-Event (PPE)** pricing, users pay a predictable micro-fee per BI query rather than paying for idle container compute units: | Event | What it covers | When it is charged | |---|---|---| | **`fcf_bi_query`** | Executing one BI tool action (`get_company_fcf_analysis`, `compare_peers_fcf`, `screen_sp500_cash_cows`, or `list`). | Once per successful query execution. Failed queries are not charged. | | **Actor start** | Starting up the Actor container for a single run. | On normal Actor runs only. Standby HTTP / MCP requests are not charged for container startup. | *** ### ⓘ Limitations and feedback - **Coverage**: Pre-cached dataset covers **516 out of 518** unique constituents across the **S\&P 500** (`503` tickers) and **Nasdaq-100** (`102` tickers). Two newly spun-off/registered entities (`HONA` and `SPCX`) do not yet have full-year 10-K filings in SEC EDGAR. - **Financial Sector Nuance**: For commercial banks and insurance companies (e.g., `JPM`, `BAC`), GAAP Operating Cash Flow includes changes in trading assets and loan originations, so FCF Conversion vs. Net Income should be interpreted alongside sector peers. - **Feedback & Feature Requests**: If you need additional XBRL metrics, quarterly (10-Q) breakdowns, or sector ratios, please submit an issue on the Actor's page in Apify Console. # Actor input Schema ## `action` (type: `string`): Choose which BI analysis or dataset action to run. ## `ticker` (type: `string`): Single US stock ticker (e.g., 'NVDA', 'AAPL', 'MSFT', 'AMZN') for get_company_fcf_analysis. ## `tickers` (type: `array`): List of tickers for side-by-side comparison (used when action = compare_peers_fcf). ## `min_fcf_margin_pct` (type: `number`): Minimum FCF Margin filter for screen_sp500_cash_cows. ## `cached_only` (type: `boolean`): When action = list, if true returns cached dataset tickers; if false returns the full S\&P 500 / QQQ 100 universe. ## Actor input object example ```json { "action": "get_company_fcf_analysis", "ticker": "NVDA", "tickers": [ "NVDA", "MSFT", "AAPL", "AMZN", "META", "GOOGL" ], "min_fcf_margin_pct": 15, "cached_only": true } ``` # Actor output Schema ## `fcfBiResults` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("chlorella2026/sp500-ndx100-fcf-mcp").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("chlorella2026/sp500-ndx100-fcf-mcp").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call chlorella2026/sp500-ndx100-fcf-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,chlorella2026/sp500-ndx100-fcf-mcp" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/oPD0eGpF6y3pCZUA4/builds/vQRFa1qeg8d9pn1OG/openapi.json