How to Use the AT&T Messaging MCP in Pydantic AI

Q: Why did my shortcode creation fail?

You likely missed a required field. The createshortcode tool demands specific parameters, and Pydantic AI will surface a loud error detailing exactly which argument was omitted.

Type-safe AT&T Messaging integration for Pydantic AI agents.

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Connect AT&T Messaging MCP to Pydantic AI

Create your Vinkius account to connect AT&T Messaging 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 AT&T Messaging with Pydantic AI

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Perplexity

Type-validated texts via MCP Server

This AT&T Messaging MCP Server enforces strict schema validation before any text leaves your system. When your agent tries to message a customer, Pydantic AI checks the request. The `send_sms` tool requires a strict E.164 format for phone numbers. If the model hallucinates a ten-digit string without the country code, the framework throws a loud validation error. You catch the mistake immediately. The same strict typing applies when attaching media URLs via `send_mms`.

Parse inbound replies with certainty

This MCP Server maps inbound customer messages to exact data fields. Reading replies requires precision. Your agent pulls the latest texts using `get_inbound_messages` and expects specific keys for the sender number, message body, and timestamp. Pydantic models guarantee the response structure. You'll never get a null value where a string should be. The agent checks `get_keyword_responses` to verify opt-out logic, knowing the data matches your exact schema.

Audit delivery states reliably

This MCP Server provides hard proof that your alerts actually reached user devices. The agent polls `get_message_status` to check receipts. Every status code gets validated against known API responses. Generating compliance logs is completely predictable. The agent runs `list_messages` and parses the output. Because the framework enforces strict types, your final audit report never contains corrupted data.

Setup guide

Set up AT&T Messaging 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": {
        "att-messaging-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent AT&T Messaging transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AT&T Messaging. 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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Common questions about AT&T Messaging MCP in Pydantic AI

Install pydantic-ai-slim with the mcp extra. Initialize MCPToolset with your Vinkius HTTP endpoint. Pass that directly into the toolsets array of your Agent instance.

The framework strictly enforces the schemas defined by the MCP tools. If a model tries passing an invalid format to send_bulk_sms, the toolset rejects it at runtime.

The framework is completely model-agnostic. You can route send_sms calls through local LLMs, Anthropic, or OpenAI without changing the toolset configuration.

You likely missed a required field. The create_shortcode tool demands specific parameters, and Pydantic AI will surface a loud error detailing exactly which argument was omitted.

Recipient E.164 numbers and text payloads traverse a zero-trust V8 Isolate Sandbox. Vinkius operates ephemerally, meaning all message bodies and media URLs vanish from memory the millisecond the AT&T API returns a response.

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