How to Use the Nue.io Revenue MCP in Pydantic AI

Q: How do I connect Pydantic AI to the Nue.io Revenue server?

You initialize the MCPToolset with your Vinkius HTTP endpoint and pass it to the agent constructor. This replaces the deprecated HTTP server classes, giving you a clean, unified MCP setup.

Q: Can I use Pydantic AI to validate automated revenue workflows?

Yes, you can pass the output of listrevenueworkflows through a custom Pydantic model. This ensures that every step in your billing pipeline matches your strict internal compliance standards.

Q: How do I check which user is running the billing queries?

The getcurrentuser tool returns the metadata of the active user. Your agent can call this to verify permissions before displaying sensitive catalog details.

Validate every product bundle and price tag at runtime with type-safe Pydantic AI agents to prevent billing pipeline crashes.

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Connect Nue.io Revenue MCP to Pydantic AI

Create your Vinkius account to connect Nue.io Revenue 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 Nue.io Revenue with Pydantic AI

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Validate price tags in Pydantic AI

`list_product_price_tags` fetches the pricing rules and values assigned to specific items. Your agent parses this data through Pydantic models to ensure every decimal place, currency code, and billing interval is perfectly formatted. If a price tag contains unexpected nulls or malformed strings, the system raises a validation error immediately. This stops corrupted pricing data from entering your execution loop.

Enforce strict schemas via the MCP Server

`get_product_details` retrieves granular metadata for a single SKU in your catalog. Your agent uses this tool to check product attributes, ensuring they match your internal database schemas before starting a transaction. This runtime validation guarantees that your agent never operates on hallucinated product IDs when calling the MCP Server. It provides a reliable bridge between your catalog and your Python application.

Audit metadata sources with type safety

`list_metadata_source_objects` maps out the source entities used for revenue tracking and CRM synchronization. Your agent inspects these mappings to verify that fields align across systems. By validating these mappings against strict Pydantic models, you catch schema drift early. This prevents silent sync failures between your financial records and external databases.

Setup guide

Set up Nue.io Revenue 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": {
        "nueio-revenue-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Nue.io Revenue transactions")
print(result.output)

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Common questions about Nue.io Revenue MCP in Pydantic AI

The framework immediately raises a ValidationError if tools like `list_product_bundles` return fields that mismatch your schemas. This prevents your agent from processing corrupt billing data or hallucinating pricing values.

You initialize the `MCPToolset` with your Vinkius HTTP endpoint and pass it to the agent constructor. This replaces the deprecated HTTP server classes, giving you a clean, unified MCP setup.

Yes, you can pass the output of `list_revenue_workflows` through a custom Pydantic model. This ensures that every step in your billing pipeline matches your strict internal compliance standards.

The `get_current_user` tool returns the metadata of the active user. Your agent can call this to verify permissions before displaying sensitive catalog details.

Your revenue workflows and catalog schemas are isolated within a zero-trust V8 sandbox on Vinkius. The MCP Server uses transient environments that discard all session data immediately after the API call completes, keeping your financial rules completely private.

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