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How to Use the Infracost MCP in Pydantic AI

Q: How do I configure the Infracost MCP Server using the unified Pydantic AI toolset?

Instantiate MCPToolset with your Vinkius HTTP endpoint URL. Pass this object into the toolsets argument of your Agent constructor.

Q: Can my Pydantic AI agent manage Infracost tagging policies?

Yes, your agent uses updatetaggingpolicy to define allowed values and uploadcustomproperties to attach metadata. Every response is parsed into type-safe Python objects.

Validate Infracost cloud cost predictions at runtime with type-safe Pydantic AI agents.

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Works with every AI agent you already use

…and any MCP-compatible client

$Infracost MCP on Cursor AI Code Editor MCP Client$ $Infracost MCP on Claude Desktop App MCP Integration$ $Infracost MCP on OpenAI Agents SDK MCP Compatible$ $Infracost MCP on Visual Studio Code MCP Extension Client$ $Infracost MCP on GitHub Copilot AI Agent MCP Integration$ $Infracost MCP on Google Gemini AI MCP Integration$ $Infracost MCP on Lovable AI Development MCP Client$ $Infracost MCP on Mistral AI Agents MCP Compatible$ $Infracost MCP on Amazon AWS Bedrock MCP Support$

MCP Servers - Free for Subscribers

Connect Infracost MCP to Pydantic AI

Create your Vinkius account to connect Infracost 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.

GDPR Free for Subscribers

Setup Infracost with Pydantic AI

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Type-safe pricing queries with Pydantic AI

The `query_pricing` tool sends GraphQL queries to fetch cloud rates, returning structured data that Pydantic AI validates instantly. If the schema changes or returns malformed data, your agent raises a validation error immediately. This runtime safety guarantees that your code never processes corrupt cost estimates. Your Python application remains stable because every price point matches your defined Pydantic models.

Strict guardrail enforcement via this MCP Server

The `create_guardrail` tool sets up financial policy boundaries that your type-safe agent monitors at runtime. Your agent uses `get_guardrail` and `list_guardrails` to check if proposed infrastructure plans violate your budget. Because Pydantic AI is model-agnostic, you can run these cost checks using OpenAI, Anthropic, or local models. The agent uses `update_guardrail` to adjust limits dynamically based on current environment budgets.

Enterprise price book validation

The `ingest_price_book` tool uploads custom pricing sheets to ensure your agent calculates costs based on your specific enterprise discounts. Your agent obtains a secure upload link via `get_price_book_files_url` and tracks progress using `get_price_book`. Once the upload completes, the agent executes `update_organization` to activate the custom price book. Pydantic AI validates the resulting organization settings to confirm the custom rates are active.

Setup guide

Set up Infracost 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": {
        "infracost-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Infracost MCP in Pydantic AI

Instantiate `MCPToolset` with your Vinkius HTTP endpoint URL. Pass this object into the `toolsets` argument of your `Agent` constructor.

The framework raises a validation error at runtime instead of allowing your agent to make decisions on corrupt data. This prevents silent failures in your deployment pipeline.

Yes, your agent uses `update_tagging_policy` to define allowed values and `upload_custom_properties` to attach metadata. Every response is parsed into type-safe Python objects.

Yes, the server must run externally. You connect to it using the HTTP or SSE transport layers configured in your `MCPToolset` initialization.

Your CSV pricing files are uploaded directly to a secure, ephemeral V8 isolate sandbox managed by Vinkius. The data is parsed strictly for your organization's cost calculations and is never exposed to external models.

Use it with your favorite AI tools

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

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