Draft loans and push them to underwriting.
Claude
ChatGPT
Cursor
Gemini
Windsurf
VS Code
JetBrains
Vercel
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
LendAPI connects your AI client directly to your loan origination system. You can pull borrower profiles, draft loan applications, and push them into automated credit decisioning without leaving your IDE.
It handles the strict sequencing of creating a borrower, drafting the loan, and submitting it for underwriting review.
What your AI can do
List loan applications
Grabs all active loan drafts and submitted applications across your pipeline.
List borrowers
Retrieves a paginated list of all borrower profiles currently in your system.
Create loan application
Drafts a new loan request and ties it to a specific borrower profile.
Add new applicants to your lending system with full profile details.
Generate new loan requests and tie them to existing borrowers.
Push completed loan drafts into the automated underwriting queue.
Check the exact underwriting stage and financial details of any active loan.
Retrieve full profile data and financial metadata for registered applicants.
Grab the current valid picklist values for industries, asset types, and loan purposes.
Ask an AI about this
Compatible AI Apps
OAuth 2.0 CompatibleWaiting for input…
LendAPI MCP Tools (8)
Manage your entire loan origination pipeline. Create borrowers, draft applications, validate metadata, and push loans to the credit decisioning engine.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using LendAPI on VinkiusList Loan Applications
Grabs all active loan drafts and submitted applications across your pipeline.
List Borrowers
Retrieves a paginated list of all borrower profiles currently in your system.
Create Loan Application
Drafts a new loan request and ties it to a specific borrower profile.
Create New Borrower
Adds a new applicant profile to the system with all required identity details.
Get Application Details
Fetches the current status, amount, and underwriting stage for a specific loan.
Get Borrower Details
Pulls the full profile and financial metadata for a single registered applicant.
Get Lendapi Picklists
Returns the currently valid dropdown values for loan purposes, industries, and asset types.
Submit Loan Application
Pushes a completed loan draft into the automated credit decisioning engine.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 8 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Copying borrower IDs between tabs all day.
You open the underwriting dashboard. You find a borrower, copy their ID, and paste it into a new loan form. You look up the valid asset types in a separate wiki, type it in, and submit. Then you switch back to your IDE to write the API wrapper for that exact flow. You repeat this for every new loan product you build.
With this connector, you just tell your AI client to draft the loan. It checks the valid metadata, creates the borrower if needed, and pushes the application to the decisioning queue. You get the exact API payload you need to replicate the flow, without ever leaving your terminal.
LendAPI MCP kills the boilerplate lending CRUD.
You no longer have to write custom fetch calls to check if a borrower exists before drafting a loan. You stop hardcoding industry codes and hoping the underwriting engine accepts them. The agent handles the strict sequencing and metadata validation automatically.
You get a direct, conversational pipeline into your loan origination system. The tedious part of lending operations disappears, leaving you to actually build the logic that matters.
What your AI can actually do with this
You spend half your day toggling between your underwriting dashboard and your code editor. You check a borrower's status, copy their ID, paste it into a loan form, fill out the asset type, and wait for the credit engine to spit out a decision. It is tedious and prone to typos.
This connector changes that. You just talk to your AI client in plain English. Tell it to pull up a specific borrower, draft a new loan for them, and push it into the decisioning queue. The system handles the strict data dependencies behind the scenes. It makes sure the borrower exists before the loan gets created, and it validates the metadata against your current picklists so the underwriting engine does not reject it for bad formatting.
Since it is hosted on Vinkius, you connect once and get immediate access to your entire lending stack from Cursor, Claude, or whatever MCP-compatible client you prefer. You stop acting like a human data entry bridge and start actually building lending logic.
019d75c6-8b9c-73ca-8948-5b67a478db81 Here's how it actually works
The bottom line is you stop writing boilerplate REST calls and just tell the agent what loan you want to process.
Connect your LendAPI account by pasting your Bearer Token into the Vinkius dashboard.
Open your preferred AI client and ask it to pull a borrower list or draft a new loan application.
Watch the agent handle the API sequencing, validate the picklists, and submit the application for decisioning.
Who is this actually for?
The backend engineer tired of writing CRUD wrappers for the lending API, and the underwriting manager who needs live pipeline data without logging into three different dashboards.
You use this to prototype loan origination flows in your IDE without spinning up Postman or writing temporary API scripts.
You ask your AI client for the status of a specific application and get the exact risk tier and borrower details instantly.
You pull daily lists of new applications and cross-reference borrower profiles to spot missing documentation before it hits the decisioning engine.
What Changes When You Connect
You stop guessing valid dropdown values. The get_lendapi_picklists tool feeds your agent the exact asset types and loan purposes, so your applications never get rejected for bad metadata.
You eliminate orphaned loan records. The agent naturally calls create_new_borrower before create_loan_application, ensuring every loan has a valid identity tied to it before submission.
You get instant visibility into the underwriting queue. Use list_loan_applications to see exactly which loans are stuck in review without leaving your terminal or IDE.
You push loans to the decisioning engine instantly. Instead of clicking through a web UI, submit_loan_application triggers the automated risk assessment the second you finish drafting.
You pull borrower history on the fly. When a loan needs manual review, get_borrower_details gives your agent the exact financial metadata it needs to spot missing documentation.
See it in action
Drafting a loan without the web UI
A developer is building a new onboarding flow. They ask their agent to use create_new_borrower for a test user, then create_loan_application for a $5,000 personal loan, and finally submit_loan_application to test the decisioning engine end-to-end.
Clearing a backlog of stuck applications
An ops manager notices a pile of loans sitting in draft status. They tell their agent to run list_loan_applications, filter for drafts older than 48 hours, and use get_application_details to see exactly what data is missing before fixing them.
Validating metadata before a bulk upload
A fintech dev is about to push 500 new loans via script. They use get_lendapi_picklists to pull the exact valid industry codes, ensuring their bulk payload matches the underwriting engine's strict formatting rules.
Checking applicant history during a call
An underwriter is on the phone with a borrower. They ask their AI client to run get_borrower_details to instantly pull the applicant's current risk profile and past loan history without tabbing over to the main dashboard.
The honest tradeoffs
Submitting a draft with missing fields
Calling submit_loan_application on a loan that lacks a required asset type or purpose code.
Always run get_lendapi_picklists first to see the exact required values. Then use create_loan_application with those exact strings. The decisioning engine will instantly reject malformed payloads.
Creating a loan for a ghost borrower
Trying to draft a loan application by passing a borrower ID that does not exist in the system yet.
You must create the identity first. Use create_new_borrower to generate the profile, grab the returned ID, and then pass that exact ID into create_loan_application. The API enforces this sequence.
Polling the decisioning engine constantly
Running get_application_details in a tight loop immediately after calling submit_loan_application.
Credit decisioning takes a few seconds. Submit the loan, wait for the webhook or check the status after a reasonable delay. Hammering the status endpoint just throttles your API rate limits.
When It Fits, When It Doesn't
Use this if you are building fintech applications that need to interact with the LendAPI loan origination engine. It is perfect for developers who need to draft applications, manage borrower identities, and trigger automated credit decisions directly from their AI client. Do not use this if you just need to read public financial news or scrape generic banking data. It is strictly for the LendAPI ecosystem. If you need to process payments or move actual money, this will not help you. It handles the application lifecycle and underwriting metadata. If your workflow requires complex multi-party document signing or physical collateral tracking, you will need a specialized document management tool instead.
Questions you might have
How do I check the status of a loan with LendAPI MCP? +
Use the get_application_details tool. It returns the exact underwriting stage, loan amount, and primary borrower for any specific application ID you pass to it.
Can LendAPI MCP create a new borrower profile? +
Yes. The create_new_borrower tool adds a new applicant to your system. You just pass the required profile details in the JSON body, and it returns the new borrower ID.
How do I push a loan to underwriting using LendAPI MCP? +
Call the submit_loan_application tool. It takes a completed loan draft and pushes it directly into the automated credit decisioning engine for risk assessment.
Does LendAPI MCP show me all active loans? +
Yes. The list_loan_applications tool retrieves your entire pipeline of active loan drafts and submitted applications across the system.
How do I know which asset types are valid in LendAPI MCP? +
Use the get_lendapi_picklists tool. It pulls the currently valid dropdown values for loan purposes, industries, and asset types so your applications do not get rejected.
How does LendAPI MCP handle authentication? +
You authenticate with a Bearer Token from your LendAPI dashboard. Enter this API key during the initial setup, and the MCP passes it in the header for every request your AI client makes.
What payload does the create_loan_application tool expect? +
It expects a JSON body with the core application details. Your agent will ask you for the loan amount, purpose, and borrower ID before formatting and sending the request to LendAPI.
Does the get_borrower_details tool return financial history? +
Yes, it pulls the full profile for a specific borrower. The response includes their contact info, registered assets, and current loan requests, giving your agent the context needed for underwriting.
How do I trigger an automated credit decision? +
Use the submit_loan_application tool with the unique application ID. This will trigger the rules-based or AI-driven decision engine configured in your LendAPI account.
Can I search for valid values for specific fields like 'purpose'? +
Yes, the get_lendapi_picklists tool allows you to retrieve the full list of allowed values for various metadata fields, ensuring your application data is compliant.
Is it possible to manage borrower profiles via the agent? +
Absolutely. You can list all borrowers, retrieve detailed profile information, and create new borrower records using the specific borrower tools provided.
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