How to Use the LendAPI MCP in Google ADK

Q: How do I add the LendAPI MCP Server to my Google ADK agent?

Install google-adk and define an McpToolset pointing to your Vinkius HTTP URL. Pass this toolset into your LlmAgent constructor to expose all eight underwriting tools to Gemini.

Q: Can my Google ADK agent query getlendapipicklists to validate inputs in LendAPI?

Yes. Your Gemini agent can call getlendapipicklists at the start of a session to learn valid dropdown values for LendAPI fields, ensuring subsequent loan creations remain error-free.

Q: Can I restrict which LendAPI MCP tools my Google ADK agent can access?

Yes, you can use the optional toolnames filter in the McpToolset configuration. This lets you restrict an agent to lookup tools like getborrowerdetails while blocking write operations.

Connect Gemini models to LendAPI using the Google ADK to analyze borrower records and write loan applications directly from your cloud.

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Setup LendAPI with Google ADK

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Analyze massive loan portfolios with Google ADK

The `list_loan_applications` tool retrieves historical application records via this MCP connection for bulk analysis. Your Gemini agent uses its million-token context window to cross-reference thousands of past decisions against current credit guidelines. By running this tool inside your Google Cloud environment, you can feed entire underwriting histories directly into Vertex AI. The agent spots risk patterns that standard database queries miss, without requiring manual exports.

Sync BigQuery data directly to this MCP Server

The `create_new_borrower` tool writes verified customer profiles directly into LendAPI. Your agent reads raw customer data from BigQuery, formats it according to your credit rules, and registers the borrower. This direct pipeline eliminates manual copy-pasting between cloud warehouses and your loan origination system. The agent handles the schema mapping on the fly, ensuring fields like income and address match your system requirements.

Submit applications for instant underwriting decisions

The `submit_loan_application` tool sends finalized credit files to the LendAPI decision engine. Your agent monitors the submission status and triggers downstream cloud tasks based on the approval or denial outcome. If an application requires manual review, the agent uses `get_application_details` to pull the specific underwriting flags. It then routes those details to your team's internal dashboard for rapid processing.

Setup guide

Set up LendAPI MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with LendAPI tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="LendAPI_agent",
    model="gemini-2.0-flash",
    instruction="You have access to LendAPI tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LendAPI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about LendAPI MCP in Google ADK

Install `google-adk` and define an `McpToolset` pointing to your Vinkius HTTP URL. Pass this toolset into your `LlmAgent` constructor to expose all eight underwriting tools to Gemini.

Yes. Your Gemini agent can call `get_lendapi_picklists` at the start of a session to learn valid dropdown values for LendAPI fields, ensuring subsequent loan creations remain error-free.

You should configure your agent's execution loop to handle HTTP 429 status codes. Since tools like `list_borrowers` scan your entire database, your agent should pace its requests during bulk migration tasks.

Yes, you can use the optional `tool_names` filter in the `McpToolset` configuration. This lets you restrict an agent to lookup tools like `get_borrower_details` while blocking write operations.

Your borrower profiles and credit application files are processed inside isolated, ephemeral V8 sandboxes. Vinkius secures your API keys and never persists any underlying financial data to disk.

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