How to Use the Genius Referrals MCP in Pydantic AI

Q: How do I set up the Genius Referrals MCP Server with Pydantic AI?

Install pydantic-ai-slimmcp and define an MCPToolset pointing to your Vinkius endpoint. Pass this toolset directly to your Pydantic AI agent to begin calling Genius Referrals tools like listreferralcampaigns.

Q: Can I use Pydantic AI to track Genius Referrals top performers safely?

Yes, your Pydantic AI agent can call listtopperformers and parse the output into a custom Pydantic model. This lets you enforce type constraints on Genius Referrals advocate conversion rates and total earnings.

Build type-safe referral workflows with Pydantic AI to validate Genius Referrals data at runtime.

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Create your Vinkius account to connect Genius Referrals 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 Genius Referrals with Pydantic AI

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Strict Pydantic AI validation for Genius Referrals

The `get_advocate_details` tool returns advocate profiles to your Pydantic AI agent via the Genius Referrals MCP Server. If the API returns a missing field or an unexpected data type, the framework raises a validation error immediately. This prevents corrupted Genius Referrals data from polluting your downstream systems. Your Pydantic AI agent can confidently process advocate records, knowing that fields like email addresses and referral codes match your expected data models exactly.

Type-safe conversion logging and tracking

The `log_referral_conversion` tool records signups and purchases using type-checked MCP payloads. Your Pydantic AI agent validates the conversion parameters before sending them to the Genius Referrals API, ensuring transaction values and advocate IDs are formatted correctly. After logging, the Pydantic AI agent calls `list_tracked_referrals` to verify the conversion was indexed. The returning Genius Referrals dataset is parsed into structured Pydantic models, making it easy to pass to other services in your stack.

Auditing payouts without silent failures

The `list_payout_requests` tool fetches pending redemptions, which your agent parses into typed structures to prevent silent failures. Pydantic AI ensures that payout amounts and advocate identifiers are strictly validated before any Genius Referrals money moves. The Pydantic AI agent checks these requests against `list_awarded_bonuses` to verify the advocate actually earned the reward. If a schema mismatch occurs during this Genius Referrals audit, the agent halts the process and alerts your team.

Setup guide

Set up Genius Referrals 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": {
        "genius-referrals-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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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 Genius Referrals. 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 Genius Referrals MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]` and define an `MCPToolset` pointing to your Vinkius endpoint. Pass this toolset directly to your Pydantic AI agent to begin calling Genius Referrals tools like `list_referral_campaigns`.

The Pydantic AI framework will raise a validation error, stopping the agent from acting on corrupted Genius Referrals data. This ensures your advocate metadata and campaign structures remain clean.

Yes, your Pydantic AI agent can call `list_top_performers` and parse the output into a custom Pydantic model. This lets you enforce type constraints on Genius Referrals advocate conversion rates and total earnings.

Yes, Pydantic AI handles async tool calls natively, allowing your agent to query `get_my_account` and `get_campaign_details` in parallel without blocking your Genius Referrals application.

Vinkius processes all MCP requests in ephemeral sandboxes, meaning your API keys and campaign details are never stored. Pydantic AI connects to the server via secure, authenticated HTTP endpoints to keep your referral data private.

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