Can it accidentally affect my entire Sinch account?

No. The integration only supports sending SMS, managing batches, and handling contact groups. It cannot modify billing, account settings, or access other Sinch services.

How does authentication work?

You provide your Service Plan ID and API Token. The integration generates a Bearer token header automatically for each request — no OAuth setup required.

What is a batch in Sinch?

A batch is a single SMS send operation that can target one or many recipients. Each batch has a unique ID and can be tracked, updated, or cancelled before delivery.

Sinch MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Sinch
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Sinch through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Sinch "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Sinch?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Sinch MCP Server

Connect your AI to Sinch, the global cloud communications platform for SMS messaging at scale.

Pydantic AI validates every Sinch tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Send Messages — Dispatch individual or bulk SMS messages to any phone number or contact group.
Delivery Tracking — Check delivery reports to see which messages were delivered, pending, or failed.
Batch Management — List, update, or cancel SMS batches before they're delivered.
Contact Groups — Create and manage contact groups for targeted campaign messaging.

The Sinch MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Sinch to Pydantic AI via MCP

Follow these steps to integrate the Sinch MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Sinch with type-safe schemas

Why Use Pydantic AI with the Sinch MCP Server

Pydantic AI provides unique advantages when paired with Sinch through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Sinch integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Sinch connection logic from agent behavior for testable, maintainable code

Sinch + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Sinch MCP Server delivers measurable value.

Type-safe data pipelines: query Sinch with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Sinch tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Sinch and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Sinch responses and write comprehensive agent tests

Sinch MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Sinch to Pydantic AI via MCP:

cancel_sms_batch

This action is irreversible for the remaining messages. Cancels a pending SMS batch

create_sms_group

Creates a new contact group

delete_sms_group

This action is irreversible. Permanently deletes a contact group

get_batch_details

Retrieves details for a specific SMS batch

get_delivery_report

Retrieves a delivery report for a specific batch

get_group_details

Retrieves details for a specific contact group

list_sms_batches

Lists recent SMS batches

list_sms_groups

Lists all contact groups

send_sms

You can provide multiple phone numbers in the "to" field. Ensure numbers are in international format (e.g., +1234567890). Sends a text message (SMS) to one or more recipients

update_sms_batch

Updates parameters of an existing SMS batch

Example Prompts for Sinch in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Sinch immediately.

"Send an SMS to +1234567890 saying 'Your order has been shipped!'"

"Get the delivery report for batch 9876."

Troubleshooting Sinch MCP Server with Pydantic AI

Common issues when connecting Sinch to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Sinch + Pydantic AI FAQ

Common questions about integrating Sinch MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Sinch MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.