How do I find my SignalWire Project ID and Token?

Log in to your [**SignalWire Dashboard**](https://signalwire.com/signin), select your Project, and navigate to **API** in the sidebar. You will find your Project ID and can generate a new API Token there.

What is the Space URL?

The Space URL is the prefix of your SignalWire domain (e.g., if your domain is `example.signalwire.com`, the Space is `example`). Enter only the prefix.

Can the agent send SMS messages?

Yes. Use the `send_sms` tool providing the recipient number, your SignalWire number, and the message body. Your agent will deliver the SMS and confirm the status instantly.

SignalWire MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: SignalWire
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect SignalWire 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 SignalWire "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in SignalWire?"
    )
    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 SignalWire MCP Server

Empower your AI agent to orchestrate your entire cloud communication infrastructure with SignalWire, the advanced platform for messaging, voice, and video. By connecting SignalWire to your agent, you transform complex telecom management into a natural conversation. Your agent can instantly list your phone numbers, audit message delivery, and retrieve call logs without you ever touching a technical console. Whether you are providing customer alerts or managing corporate voice lines, your agent acts as a real-time telecom operator, ensuring your communication is always reliable and your usage data is organized.

Pydantic AI validates every SignalWire tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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

Messaging Intelligence — Send SMS messages instantly and retrieve detailed message status and history.
Call Auditing — List all recent voice calls and retrieve metadata for each, including direction and duration.
Number Oversight — List and monitor all incoming phone numbers associated with your project.
Usage Intelligence — Retrieve detailed usage records to maintain strict organizational control over your communication costs.
Account Governance — Monitor account-wide metadata to understand your project status in real-time.

The SignalWire MCP Server exposes 8 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 SignalWire to Pydantic AI via MCP

Follow these steps to integrate the SignalWire 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 8 tools from SignalWire with type-safe schemas

Why Use Pydantic AI with the SignalWire MCP Server

Pydantic AI provides unique advantages when paired with SignalWire 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 SignalWire integration code

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

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

SignalWire + Pydantic AI Use Cases

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

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

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

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

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

SignalWire MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect SignalWire to Pydantic AI via MCP:

get_account_info

Get SignalWire account details

get_call

Get details for a specific call

get_message

Get details for a specific message

list_calls

List recent voice calls

list_messages

List recent SMS/MMS messages

list_phone_numbers

List SignalWire phone numbers

list_usage

Get account usage records

send_sms

Send an SMS message

Example Prompts for SignalWire in Pydantic AI

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

"List all my SignalWire phone numbers."

"Send SMS 'Server alert: high usage detected' to +15550123."

"Show me recent call logs for my project."

Troubleshooting SignalWire MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

SignalWire + Pydantic AI FAQ

Common questions about integrating SignalWire 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 SignalWire MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.