# FDD Parsed Financials — Franchise Money Facts (`querymill/fdd-parsed-financials`) Actor

Parsed money facts from a brand's filed Franchise Disclosure Document: Item 5/6 fees, Item 7 all-in investment range (cover-verified), Item 19 representations where disclosed, Item 20 outlet trend. $0.35/report; no charge on a miss.

- **URL**: https://apify.com/querymill/fdd-parsed-financials.md
- **Developed by:** [Eric Trammell](https://apify.com/querymill) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$350.00 / 1,000 fdd parsed financials reports

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## 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

## FDD Parsed Financials — Franchise Disclosure Document Money Facts

For a franchise brand, get the money facts from its current Franchise Disclosure Document (FDD) as structured data — parsed from the filed document itself, not scraped from marketing pages:

- **Item 5** — initial fees (including the initial franchise fee where disclosed as a single figure)
- **Item 6** — other fees: the royalty and marketing/brand-fund rows, with the FDD's own row text
- **Item 7** — the all-in estimated initial investment range, cross-verified two ways (see Accuracy)
- **Item 19** — whether the franchisor makes financial performance representations, plus a clearly-labeled average/median gross-sales figure where one could be extracted unambiguously
- **Item 20** — Table No. 1 total outlets for the last three fiscal years, with the 3-year change and trend (growing / flat / shrinking)

**Price: $0.35 per report.** One report = one brand. A brand that is not in the corpus returns `found: false` and **charges nothing** — this actor never guesses.

### Input

- `brand` — the franchise brand name, e.g. `McDonald's`, `The UPS Store`, `Tropical Smoothie Cafe`.
- `mode` — `report` (default, $0.35 on a hit) or `list` (free: returns the brands currently in the corpus, with year and investment range for each).

### Accuracy is the product

Franchise buyers make $150k–$1M+ commitments off these numbers, so the corpus is built under a strict gate. A brand enters the corpus only if **all** of these verify in its filed FDD:

1. the issuance date is found;
2. the cover page's total-investment range is found;
3. **the identical range appears as an Item 7 TOTAL inside Item 7** (cover ↔ Item 7 cross-verification);
4. Item 20 Table No. 1 total-outlet figures parse for all three fiscal years.

Documents that fail any check are excluded entirely — at launch, 13 of 27 candidate FDDs were excluded this way. Before launch, a sample of the surviving brands was verified field-by-field against the source PDFs (investment ranges, fees, royalty/marketing rows, outlet counts), and any figure that could not be verified in context was removed rather than shipped.

Every report cites its source document — brand, FDD year, issuance date, and the document itself — and carries this instruction: **as filed — verify against the source document.**

### Corpus at launch

14 brands, from their 2026 FDDs (2024 for Pet Supplies Plus): Anytime Fitness · Budget Blinds · Domino's · Dunkin' · Great Clips · Jersey Mike's Subs · McDonald's · Nothing Bundt Cakes · Pet Supplies Plus · Planet Fitness · SERVPRO · Snap-on Tools · The UPS Store · Tropical Smoothie Cafe. Use `mode: list` for the live inventory.

FDDs refile once a year, so the corpus refreshes on an annual cycle, with new brands added as their documents pass the gate.

### Sources

The corpus documents are the franchisors' state-filed FDDs — the same documents filed with state franchise regulators (Wisconsin DFI, Minnesota Commerce CARDS, California DFPI, NASAA EFD states) — obtained from a public FDD archive mirror, because the state portals themselves block automated access. Each report names the exact document it was parsed from.

### Not advice

This actor reproduces figures as filed in the FDD. It is not investment, legal, or financial advice, and no report replaces reading the full FDD — exhibits, state addenda, and item notes included.

# Actor input Schema

## `brand` (type: `string`):

Franchise brand name, e.g. McDonald's or The UPS Store. A report ($0.35) is produced only when the brand's filed FDD is in the parsed corpus; otherwise found:false and no charge.

## `mode` (type: `string`):

report = parsed FDD money facts for one brand ($0.35 per report; no charge when the brand is not in the corpus). list = free corpus inventory.

## Actor input object example

```json
{
  "brand": "McDonald's",
  "mode": "report"
}
```

# Actor output Schema

## `overview` (type: `string`):

No description

## `items` (type: `string`):

No description

## `itemCount` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "brand": "McDonald's"
};

// Run the Actor and wait for it to finish
const run = await client.actor("querymill/fdd-parsed-financials").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "brand": "McDonald's" }

# Run the Actor and wait for it to finish
run = client.actor("querymill/fdd-parsed-financials").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 '{
  "brand": "McDonald'\''s"
}' |
apify call querymill/fdd-parsed-financials --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,querymill/fdd-parsed-financials"
        }
    }
}
```

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 <APIFY_API_TOKEN>` 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/vfSThLNDl9Xl5D2pF/builds/eCZRmjRGzCycK3LoS/openapi.json