How to Use the ProUni Eligibility Calculator MCP in Pydantic AI

Build reliable ProUni eligibility logic with Pydantic AI for guaranteed data correctness.

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Connect ProUni Eligibility Calculator MCP to Pydantic AI

Create your Vinkius account to connect ProUni Eligibility Calculator to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup ProUni Eligibility Calculator with Pydantic AI

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Claude

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Gemini

Grok

Calculate Scholarship Status on the MCP Server

The `calculate_per_capita_income` tool takes gross family income and household size to generate a precise per capita figure. This output feeds into the `determine_eligibility_tier` tool, which sets the scholarship status (Full or Partial) based on fixed thresholds. Because Pydantic validates every response, you're guaranteed that the tier determination step will return data in the expected format—no silent failures.

Identify Available Courses using Pydantic AI

To narrow down options, use `identify_eligible_courses`. This tool factors in ENEM scores and public school status while respecting the scholarship tier. It tells you which courses are actually open to the student. The type-safe nature of this MCP ensures that even if a scoring system changes slightly, your agent will fail loudly with an error instead of miscalculating recommendations.

Complete Eligibility Check via Pydantic AI

After establishing eligibility and courses, you can use `query_university_locations` to find participating universities by city. This completes the full application process logic. By combining all four tools into one workflow, your agent builds a single, highly dependable calculation that requires no manual verification.

Setup guide

Set up ProUni Eligibility Calculator 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": {
        "prouni-eligibility-calculator-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent ProUni Eligibility Calculator 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 ProUni Eligibility Calculator. 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 ProUni Eligibility Calculator MCP in Pydantic AI

Pydantic validates every MCP response against defined models. If the underlying tool returns unexpected or malformed data, your agent fails immediately and loudly, pointing exactly to the issue.

The system processes quantitative financials like gross family income and household size. It’s built around maintaining strict data type adherence for accurate tiering.

Yes, because of the runtime validation layer. You get structured, predictable outputs at every single step—from income calculation to final course recommendation.

It manages complexity by enforcing schemas across tool calls. This means the output of `determine_eligibility_tier` *must* be in a format that `identify_eligible_courses` can consume, preventing logical gaps.

The server validates numbers (income, scores), strings (city names), and structured enums for eligibility tiers. This guarantees structural integrity across all tool calls.

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