Integration
Connect Feathery to Amazon Textract
When Data Received fires in Feathery, your agent runs Analyze Invoice or Receipt in Amazon Textract. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want Feathery and Amazon Textract to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)Example flows
What Feathery can start in Amazon Textract
When Data Received in Feathery
then Analyze Invoice or Receipt in Amazon Textract
When Form Completion in Feathery
then Ask Questions About a Document in Amazon Textract
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with Feathery and Amazon Textract
Triggers and actions 2 triggers · 14 actions
Trigger
Data ReceivedTriggers when an end user submits or updates data on a Feathery form.
Trigger
Form CompletionTriggers when an end user completes a Feathery form.
Action
Create Hidden FieldCreates a hidden field in your Feathery account.
Action
Create or Fetch UserCreates a Feathery end user with the given ID, or returns the existing user, including its SDK key.
Action
Create or Update SubmissionSets field values for a Feathery user and initializes submissions on the given forms.
Action
Delete UserDeletes a Feathery end user and their submissions.
Action
Get User Field DataReturns every field value a Feathery user submitted across forms.
Action
Get User Form SessionReturns a Feathery user's form session: every form they are working on and their progress.
Action
List Document TemplatesReturns document templates uploaded by your Feathery team, optionally filtered by name or tags.
Action
List FormsReturns your Feathery forms, optionally filtered by tags or active status.
Action
List Form SubmissionsReturns submissions for a Feathery form, optionally filtered by user, completion and update time.
Action
List Hidden FieldsReturns all hidden fields in your Feathery account.
Action
List UsersReturns your Feathery end users, optionally filtered by creation time or a field value.
Action
Analyze Invoice or ReceiptReads an invoice or receipt stored in S3 and returns its summary fields (vendor, date, totals) and its line items.
Action
Ask Questions About a DocumentAnswers plain-language questions about a document stored in S3, such as "What is the invoice number?", and returns each answer with its confidence.
Action
Extract Text from DocumentReads the printed and handwritten text in an image or single-page PDF stored in S3 and returns it as plain text and lines.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
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More into Amazon Textract
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Google Sheets to Amazon TextractGoogle Sheets is Google's online spreadsheet app for creating, editing and sharing spreadsheets.
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Questions
Feathery and Amazon Textract, answered
What can start an automation from Feathery?
Any of Feathery's 2 triggers in the catalog, including Data Received and Form Completion. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Amazon Textract when something happens in Feathery?
Any of Amazon Textract's 3 actions, including Analyze Invoice or Receipt, Ask Questions About a Document and Extract Text from Document. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Amazon Textract to Feathery?
Amazon Textract has no triggers in the catalog today, so automations start in Feathery. If you need the other direction, ask: your agent reads Amazon Textract's API documentation and adds it.
Do I have to build a connector for Feathery or Amazon Textract?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
Can my AI client use Feathery and Amazon Textract without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.