Integration
Connect Pipefile to Azure Form Recognizer
When File Request Created fires in Pipefile, your agent runs Analyze Invoice in Azure Form Recognizer. 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 Pipefile and Azure Form Recognizer 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 Pipefile can start in Azure Form Recognizer
When File Request Created in Pipefile
then Analyze Invoice in Azure Form Recognizer
When File Request Created in Pipefile
then Analyze Document in Azure Form Recognizer
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 Pipefile and Azure Form Recognizer
Triggers and actions 1 trigger · 16 actions
Trigger
File Request CreatedTriggers when a file request is created.
Action
Add File Request From TemplateCreate a new file request from an existing template for one recipient (name/email/phone), optionally on behalf of a team member via X-Pipefile-On-Behalf-Of.
Action
Create ContactAdd to contacts
Action
Delete ContactDelete a contact by id. Returns 204 No Content on success.
Action
Get ContactRetrieve one contact by id.
Action
Get File RequestRetrieve detailed information about one file request by id, including contents, items, files, and tracking events.
Action
List ContactsRetrieve a paginated list of contacts, filterable by name/email/phone partial match.
Action
List File Request TemplatesRetrieve the list of file request templates available for creating new file requests, with optional name search.
Action
Search File RequestsFinds all file requests matching this search query (contact name, email, tags, etc).
Action
Send RequestCreate and send a new request
Action
Update ContactUpdate name/email/phone of an existing contact by id.
Action
Analyze DocumentAnalyzes a document with a prebuilt or custom model (layout, invoice, receipt, ID, tax form and more) and returns its text, fields, tables and key-value pairs.
Action
Analyze InvoiceExtracts the key details of an invoice: vendor, customer, invoice number, dates, totals, tax and line items.
Action
Analyze ReceiptExtracts the key details of a sales receipt: merchant, date and time, subtotal, tax, tip, total and line items.
Action
Extract Document LayoutExtracts the text, tables, paragraphs and structure of a document, optionally as Markdown.
Action
Get Document ModelReturns a document model's details, including the document types it recognizes and the fields each one extracts.
Action
List Document ModelsReturns the prebuilt and custom document models available in your resource.
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
What our customers say
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Questions
Pipefile and Azure Form Recognizer, answered
What can start an automation from Pipefile?
Any of Pipefile's 1 trigger in the catalog, including File Request Created. Describe the moment in plain language and your agent picks the right one.
What can your agent do in Azure Form Recognizer when something happens in Pipefile?
Any of Azure Form Recognizer's 6 actions, including Analyze Document, Analyze Invoice, Analyze Receipt and Extract Document Layout. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Azure Form Recognizer to Pipefile?
Azure Form Recognizer has no triggers in the catalog today, so automations start in Pipefile. If you need the other direction, ask: your agent reads Azure Form Recognizer's API documentation and adds it.
Do I have to build a connector for Pipefile or Azure Form Recognizer?
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 Pipefile and Azure Form Recognizer 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.