How to Use the Corrently Regional Green Index MCP in Pydantic AI

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Connect Corrently Regional Green Index MCP to Pydantic AI

Create your Vinkius account to connect Corrently Regional Green Index 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 Corrently Regional Green Index with Pydantic AI

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Type-safe energy prices in Pydantic AI

The `get_energy_market_data` tool returns data that your agent validates against Pydantic models. You catch any API drift before it causes a runtime crash. This ensures your agent logic always works with the exact fields it expects. If the market data schema changes, your Pydantic AI agent fails immediately with a clear validation error.

Validate green index in Pydantic AI

Your agent calls `get_regional_green_index` and checks the result against your strict type definitions. This makes handling grid forecasts reliable and predictable. No more guessing if the API returned a string or a float. Pydantic AI handles the type enforcement for you, keeping your agent logic rock-solid.

Connect MCP tools to Pydantic AI

Use the MCPToolset to register this server with your agent. The setup is unified, replacing older, fragmented HTTP connection methods. Once connected, your Pydantic AI agent can use the tools like native functions. It keeps your codebase clean while adding real-time energy insights.

Setup guide

Set up Corrently Regional Green Index 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": {
        "corrently-regional-green-index-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Corrently Regional Green Index transactions")
print(result.output)

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Common questions about Corrently Regional Green Index MCP in Pydantic AI

Define a Pydantic model for the tool response. Pydantic AI automatically validates the MCP server output against your schema at runtime.

Yes, you can use SSE or Streamable HTTP transports. The MCPToolset handles the connection regardless of the transport method.

The agent raises a validation error immediately. This prevents corrupted data from entering your system and allows you to handle the failure gracefully.

The framework is model-agnostic. Whether you use OpenAI or a local model, your Pydantic AI agent treats the MCP tool output the same way.

The server connection is ephemeral and handled via a single endpoint token. Your Pydantic AI agent only reads public grid data, ensuring no sensitive local variables are leaked.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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