# Export an Airtable data dictionary as Markdown

**Use case:** 

Produce a Markdown data dictionary for an Airtable base: every table, every field, its type, its configuration and its description, with a contents list and the ER diagram as a fenced Mermaid block. Formulas are printed with real field names rather than the field IDs Airtable's API returns, so the document is readable without cross-referencing anything.

## Input

```json
{
  "baseIds": [],
  "format": "markdown",
  "includeViews": true,
  "maxTablesInDiagram": 40
}
```

## Output

```json
{
  "baseName": {
    "label": "Base",
    "format": "text"
  },
  "tableName": {
    "label": "Table",
    "format": "text"
  },
  "tableDescription": {
    "label": "Description",
    "format": "text"
  },
  "fieldCount": {
    "label": "Fields",
    "format": "number"
  },
  "viewCount": {
    "label": "Views",
    "format": "number"
  },
  "primaryFieldName": {
    "label": "Primary field",
    "format": "text"
  },
  "primaryFieldType": {
    "label": "Primary type",
    "format": "text"
  },
  "relationshipCount": {
    "label": "Relationships",
    "format": "number"
  },
  "relatedTables": {
    "label": "Linked to",
    "format": "array"
  },
  "linkFieldCount": {
    "label": "Link fields",
    "format": "number"
  },
  "oneWayLinkCount": {
    "label": "One-way links",
    "format": "number"
  },
  "selfLinkCount": {
    "label": "Self links",
    "format": "number"
  },
  "formulaFieldCount": {
    "label": "Formulas",
    "format": "number"
  },
  "rollupFieldCount": {
    "label": "Rollups",
    "format": "number"
  },
  "lookupFieldCount": {
    "label": "Lookups",
    "format": "number"
  },
  "countFieldCount": {
    "label": "Counts",
    "format": "number"
  },
  "invalidComputedFieldCount": {
    "label": "Broken computed fields",
    "format": "number"
  },
  "tableHasDescription": {
    "label": "Has description",
    "format": "boolean"
  },
  "fieldsWithDescription": {
    "label": "Described fields",
    "format": "number"
  },
  "markdownUrl": {
    "label": "Data dictionary",
    "format": "link"
  },
  "htmlUrl": {
    "label": "Page",
    "format": "link"
  },
  "diagramUrl": {
    "label": "Diagram source",
    "format": "link"
  },
  "source": {
    "label": "Source",
    "format": "text"
  },
  "collectedAt": {
    "label": "Collected",
    "format": "date"
  },
  "baseId": {
    "label": "Base ID",
    "format": "text"
  },
  "tableId": {
    "label": "Table ID",
    "format": "text"
  }
}
```

## About this Actor

This example demonstrates how to use [Airtable Base Documentation & ER Diagram Generator](https://apify.com/mediocre_interest/airtable-base-documentation.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/mediocre_interest/airtable-base-documentation.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/mediocre_interest/airtable-base-documentation.md

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`).