How to Use the Twilio MCP in OpenAI Agents SDK
Manage communications and data workflows with OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Twilio MCP to OpenAI Agents SDK
Create your Vinkius account to connect Twilio to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Managing Phone Calls via MCP Server
You can initiate outbound calls using `create_voice_call`. This tool requires a caller ID, the receiver's number, and a TwiML URL for instructions. Need to cut off a call? Use `cancel_active_call` to terminate any ongoing voice conversation immediately. It’s fast and direct.
Checking Account Usage with OpenAI Agents SDK
See your spending history by calling `get_usage_records`. This provides full usage statistics and billing records for the account. Want to know what numbers you own? Running `list_phone_numbers` shows every incoming number associated with your master Twilio account.
Sending Messages via MCP Server
Send an SMS using `send_sms`. Just provide the sender's E.164 number and the target receiver’s E.164 number, and you're set. Did someone send a message you don't want? The `delete_message` tool permanently removes the record; remember this action is irreversible.
Set up Twilio MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Twilio tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Twilio tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Twilio tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="Twilio Agent",
instructions="You have access to Twilio tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Twilio. 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Twilio MCP in OpenAI Agents SDK
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