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How to Use the Blueshift MCP in Pydantic AI

Use Blueshift with Pydantic AI to enforce strict type safety on every marketing data request.

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Connect Blueshift MCP to Pydantic AI

Create your Vinkius account to connect Blueshift 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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Type-safe customer lookups for Pydantic AI

The `get_customer` tool returns data that your agent validates against Pydantic models. If the API returns junk, the agent stops immediately. This prevents silent errors in your marketing logic. You get predictable behavior every time the agent interacts with your customer records.

Validate event history with Pydantic AI

When you call `get_event_history`, the response is parsed into your defined schema. It ensures your agent only acts on valid, well-structured historical data. You eliminate hallucinated fields before they reach your downstream systems. It is the safest way to handle external API responses.

Manage catalogs in Pydantic AI

Use `list_catalogs` to pull your inventory data into a type-safe agent flow. The framework checks every item against your model at runtime. This is ideal for production systems where correctness is non-negotiable. Your agent stays in sync with your actual catalog structure.

Setup guide

Set up Blueshift MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 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": {
        "blueshift-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Blueshift. 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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place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Blueshift MCP in Pydantic AI

You use the MCPToolset class to connect to the server. Add it to your agent's toolsets list to start performing type-safe operations.
The agent throws a validation error immediately. This stops corrupted data from propagating through your system.
Yes, it works with both Streamable HTTP and SSE. Just ensure the server is running and accessible to your local environment.
The framework is model-agnostic. You can connect local LLMs to this MCP Server as long as they support the Pydantic AI tool calling interface.
Data is validated against your schema in memory. No customer profile records are persisted on our servers, ensuring your data remains isolated.

Start using the Blueshift MCP today

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