How to Use the HighRadius MCP in Pydantic AI

Q: How does Pydantic AI work with the HighRadius MCP server?

It's simple. You pip install "pydantic-ai-slimmcp", then create an MCPToolset with your server URL. Pydantic AI uses the server's OpenAPI spec to generate models on the fly, ensuring every API call and response is type-checked.

Q: What happens if the HighRadius API returns an unexpected response with Pydantic AI?

Your agent will raise a ValidationError immediately. This is the main benefit—it prevents your agent from making decisions based on incomplete or malformed data, which is critical for financial applications.

Q: Can I use Pydantic AI and HighRadius to reconcile a single payment against multiple invoices?

Yes. The reconcilepayment tool is designed for this. You provide the paymentid and an array of invoiceids, and Pydantic AI ensures your input matches the required schema before making the call.

Q: How do I create a payment dispute in HighRadius with a Pydantic AI agent?

Your agent will call the createdispute tool. Pydantic AI validates that the agent provides the required invoiceid, reason, and amount fields, so you don't send a bad request to the HighRadius API.

Build type-safe financial agents with Pydantic AI. Enforce correctness when managing HighRadius invoices, payments, and disputes.

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Connect HighRadius MCP to Pydantic AI

Create your Vinkius account to connect HighRadius to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup HighRadius with Pydantic AI

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Perplexity

Prevent Data Corruption

This is all about correctness. When your agent calls `get_invoice` or `get_payment`, Pydantic AI validates the entire response against a strict schema. No more silent failures from unexpected API changes. If HighRadius returns a field in the wrong format or misses a required key, your agent stops cold with a `ValidationError`. You'll know immediately that something is wrong, preventing bad data from hitting your books.

Reliably Reconcile and Dispute

Build an agent you can actually trust with financial operations. Use `list_payments` to find new payments and `list_invoices` to find their matching receivables. Because every tool call is validated, you can be confident that the IDs you pass to `reconcile_payment` are correct. The same goes for creating disputes—your agent uses a validated model to call `create_dispute`, ensuring the payload is always right.

Model-Agnostic HighRadius MCP Server

Use any LLM you want—OpenAI, Anthropic, a local model—Pydantic AI doesn't care. This HighRadius MCP server exposes a standard set of tools that work everywhere. Just point the `MCPToolset` at the Vinkius URL. Your agent gets instant, validated access to your AR data. It's the fastest way to build a financial agent that you know won't fail silently.

Setup guide

Set up HighRadius MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "highradius-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to HighRadius tools.",
)

result = await agent.run("List recent HighRadius transactions")
print(result.output)

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Common questions about HighRadius MCP in Pydantic AI

It's simple. You `pip install "pydantic-ai-slim[mcp]"`, then create an `MCPToolset` with your server URL. Pydantic AI uses the server's OpenAPI spec to generate models on the fly, ensuring every API call and response is type-checked.

Your agent will raise a `ValidationError` immediately. This is the main benefit—it prevents your agent from making decisions based on incomplete or malformed data, which is critical for financial applications.

Yes. The `reconcile_payment` tool is designed for this. You provide the `payment_id` and an array of `invoice_ids`, and Pydantic AI ensures your input matches the required schema before making the call.

Your agent will call the `create_dispute` tool. Pydantic AI validates that the agent provides the required `invoice_id`, `reason`, and `amount` fields, so you don't send a bad request to the HighRadius API.

Security is strict. The MCP server processes only the specific invoice, payment, and customer data needed for a given tool call. Pydantic's validation adds another layer by rejecting any unexpected data fields, and all connections are encrypted and isolated.

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