Integration
Connect MRPLN to Nanonets OCR
When Customer Updated (instant) fires in MRPLN, your agent runs Add training images by file in Nanonets OCR. 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 MRPLN and Nanonets OCR 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 MRPLN can start in Nanonets OCR
When Customer Updated (instant) in MRPLN
then Add training images by file in Nanonets OCR
When New Customer in MRPLN
then OCR With File in Nanonets OCR
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 MRPLN and Nanonets OCR
Triggers and actions 6 triggers · 16 actions
Trigger
Campaign Launched (instant)Fires instantly when a campaign is launched (campaign.launched).
Trigger
Customer Opted Out (instant)Fires instantly when a customer opts out (customer.opted_out).
Trigger
Customer Updated (instant)Triggers instantly when a customer is updated in MRPLN.
Trigger
Message Sent (instant)Fires instantly when a message is queued or scheduled for a customer (message.sent).
Trigger
New CustomerTriggers when a new customer is added.
Trigger
New Customer (instant)Triggers instantly when a customer is created in MRPLN.
Action
Create CustomerCreates a new customer in MRPLN.
Action
Find CustomerFinds a customer by email address. Returns the first matching customer, or found=false when none match.
Action
Find Customer by PhoneFind a customer by their SMS phone number.
Action
Find Customer by WhatsAppFind a customer by their WhatsApp number.
Action
List TemplatesList the approved message templates for a channel.
Action
Send Message to CustomerSend an email, SMS, or WhatsApp message to a customer using an approved template
Action
Trigger CampaignLaunch a campaign that was built in MRPLN.
Action
Update CustomerUpdates an existing customer in MRPLN.
Action
Add training images by fileUpload training images from local files.
Action
Add training images by URLUpload training images by URLs.
Action
OCR With FileUses Nanonets OCR to extract text
Action
OCR With File (Asynchronous)Uses Nanonets OCR to extract text asynchronously. Results will appear via the trigger
Action
OCR With File (Tables Included)Uses Nanonets OCR to extract text including line items. Results will appear via the trigger
Action
OCR With File (Tables Included) - Document Level ResponseUses Nanonets OCR to extract text including line items. Results will appear via the trigger
Action
OCR With URLSync prediction for image/document URLs.
Action
OCR With URL (Asynchronous)Async prediction for public file URLs.
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
MRPLN and Nanonets OCR, answered
What can start an automation from MRPLN?
Any of MRPLN's 6 triggers in the catalog, including Customer Updated (instant), New Customer, New Customer (instant) and Campaign Launched (instant). Describe the moment in plain language and your agent picks the right one.
What can your agent do in Nanonets OCR when something happens in MRPLN?
Any of Nanonets OCR's 8 actions, including Add training images by file, Add training images by URL, OCR With File and OCR With File (Asynchronous). Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from Nanonets OCR to MRPLN?
Nanonets OCR has no triggers in the catalog today, so automations start in MRPLN. If you need the other direction, ask: your agent reads Nanonets OCR's API documentation and adds it.
Do I have to build a connector for MRPLN or Nanonets OCR?
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 MRPLN and Nanonets OCR 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.