How to Use the AP Elections API MCP in Pydantic AI

Validate live AP election data at runtime with type-safe Pydantic AI agents.

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Connect AP Elections API MCP to Pydantic AI

Create your Vinkius account to connect AP Elections API 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 AP Elections API with Pydantic AI

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Strict validation of AP Elections API data in Pydantic AI

The `get_election_results` tool returns raw vote counts that Pydantic AI immediately validates against strict schema models at runtime. If the AP API returns an unexpected data type, your agent raises a validation error instantly instead of passing corrupt data down the line. This strict approach ensures your dashboards never display broken calculations. You catch schema drift the second it happens, making your election tracking system highly dependable.

Check API status safely using this MCP Server

The `check_api_status` tool gives your Pydantic AI agent a type-safe way to confirm the AP feed is online. The agent parses the status response into a validated boolean, ensuring your pipeline only runs when the source is healthy. By wrapping this check in a Pydantic model, you guarantee your code behaves predictably. Your agent won't crash on unhandled null values if the AP servers undergo maintenance.

Extract candidate and race details with type safety

The `list_election_candidates` and `get_race_details` tools pull structured information on candidates and specific voting races. Pydantic AI enforces type boundaries on fields like candidate IDs and vote percentages, preventing your agent from hallucinating data. You register the MCP Server using the unified `MCPToolset` class. This allows your agent to query race breakdowns and format them into clean, verified Python objects for your downstream services.

Setup guide

Set up AP Elections API 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": {
        "ap-elections-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent AP Elections API transactions")
print(result.output)

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Common questions about AP Elections API MCP in Pydantic AI

Use the MCPToolset constructor with your Vinkius HTTP endpoint, then pass it to the toolsets argument when initializing your Pydantic AI Agent.

Pydantic AI fails loudly by raising a validation error at runtime, preventing your agent from processing corrupted candidate names or incorrect vote counts.

Yes. Pydantic AI handles async calls natively, letting your agent run `get_race_details` concurrently across multiple races to speed up your data collection.

Yes. Pydantic AI is model-agnostic, meaning you can switch between OpenAI, Anthropic, or local models while utilizing the exact same election data tools.

Vinkius manages the MCP Server in an ephemeral, zero-trust sandbox, meaning your API tokens and specific race queries are processed in memory and never logged or stored.

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