How to Use the BLS Prices — Consumer Price Index (CPI) & Inflation MCP in Pydantic AI

Type-safe inflation data for your Pydantic AI agent workflows.

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Connect BLS Prices — Consumer Price Index (CPI) & Inflation MCP to Pydantic AI

Create your Vinkius account to connect BLS Prices — Consumer Price Index (CPI) & Inflation 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 BLS Prices — Consumer Price Index (CPI) & Inflation with Pydantic AI

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Validate CPI data in Pydantic AI

Use `get_cpi_inflation` to pull baseline numbers directly into your typed models. If the data structure changes, your agent fails clearly instead of guessing. This keeps your application logic stable. You define the schema, and the framework enforces it on every tool response.

Access BLS series via Pydantic AI

Call `query_bls` to get precise price history. Your agent wraps the output in Pydantic models to ensure every field is exactly what you expect. This prevents silent corruption in your data pipelines. You get clean, validated inputs for your downstream analysis.

Build reliable agents with Pydantic AI

Ensure your agent only acts on verified inflation metrics. The framework validates the tool output at runtime before it reaches your logic. This MCP Server provides the raw data, and your models provide the safety. It is the best way to handle external economic data in a production system.

Setup guide

Set up BLS Prices — Consumer Price Index (CPI) & Inflation 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": {
        "bls-prices-consumer-price-index-cpi-inflation-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to BLS Prices — Consumer Price Index (CPI) & Inflation tools.",
)

result = await agent.run("List recent BLS Prices — Consumer Price Index (CPI) & Inflation transactions")
print(result.output)

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Common questions about BLS Prices — Consumer Price Index (CPI) & Inflation MCP in Pydantic AI

Add the MCPToolset to your agent configuration. Your tools will automatically validate responses against your Pydantic models for maximum reliability.

Only if the API returns unexpected data. Because Pydantic AI enforces strict typing, the agent will catch the mismatch and stop execution immediately.

The server transmits the data directly to your agent. Your session is isolated, and the Vinkius infrastructure ensures no data is cached or stored.

Yes. You can connect using Streamable HTTP or SSE transports. Just define the URL in your MCPToolset instance.

Yes. Every response from the server is checked against your defined models at runtime. It eliminates hallucinated fields and keeps your data consistent.

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