Does Retell handle the telephone lines, or do I need my own Twilio/carrier?

Retell AI is designed to integrate seamlessly into telephony workflows but generally focuses on the conversational agent side. They provide features to list and attach numbers (`list_phone_numbers`), but you often purchase those numbers or link a custom SIP trunk through Retell accounts. You can run `list_phone_numbers` to see your currently available direct lines.

How do I create an outbound call programmatically with my assistant?

Simply ask your assistant to "Call X using my Y agent." Behind the scenes, the AI relies on the `create_phone_call` tool, transmitting a JSON payload supplying the `from_number` (a Retell registered phone number), `to_number` (destination), and an `override_agent_id` parameter to assign your voice agent correctly.

Can the AI initiate voice calls in a web browser instead of over the phone?

Yes. Use the `register_web_call` tool to create a browser-based voice session. This returns a connection URL and access token that your frontend application can use to start a real-time WebRTC conversation with a Retell voice agent, without requiring any phone line.

Retell AI MCP Server for Google ADK 10 tools — connect in under 2 minutes

Name: Retell AI
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Retell AI as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

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

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="retell_ai_agent",
    instruction=(
        "You help users interact with Retell AI "
        "using 10 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Retell AI MCP Server

Connect your conversational assistant directly to Retell AI, a powerful platform for building voice-driven conversational agents. Empower your AI to orchestrate, analyze, and automate phone calls or web-based voice interactions seamlessly via simple text commands. From provisioning intelligent voice agents to placing outbound calls to customers, this integration brings the full telecommunication stack directly to your chat interface.

Google ADK natively supports Retell AI as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Automate Phone Calls — Command your assistant to initiate outbound voice interactions on your behalf (create_phone_call) or register active sessions for web browser integration (register_web_call).
Build and Manage Voice Agents — Dynamically orchestrate AI agent personalities (create_agent, update_agent) and configure their underlying conversational brain (create_llm) with specific system instructions and models.
Analyze Telemetry — Keep track of your infrastructure by querying historical call logs (list_calls), investigating specific conversations for transcripts and sentiment analysis (get_call_details), surveying available text-to-speech voices (list_voices), and reviewing provisioned communication lines (list_phone_numbers and list_agents).

The Retell AI MCP Server exposes 10 tools through the Vinkius. Connect it to Google ADK 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 Retell AI to Google ADK via MCP

Follow these steps to integrate the Retell AI MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 10 tools from Retell AI via MCP

Why Use Google ADK with the Retell AI MCP Server

Google ADK provides unique advantages when paired with Retell AI through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Retell AI

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Retell AI tools with BigQuery, Vertex AI, and Cloud Functions

Retell AI + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Retell AI MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Retell AI and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Retell AI tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Retell AI regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Retell AI

Retell AI MCP Tools for Google ADK (10)

These 10 tools become available when you connect Retell AI to Google ADK via MCP:

create_agent

Creates a new AI voice agent

create_llm

Configures a Retell-hosted LLM

create_phone_call

Provide a JSON payload with "from_number" and "to_number". Initiates an outbound phone call

get_call_details

Retrieves details for a specific call

list_agents

Lists all configured AI voice agents

list_calls

Lists all historical and active calls

list_phone_numbers

Lists all phone numbers associated with the account

list_voices

Lists all available text-to-speech voices

register_web_call

Registers a new web-based call

update_agent

Updates an existing AI voice agent

Example Prompts for Retell AI in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Retell AI immediately.

"Can you show me the transcripts for call ID `c_f3a123`?"

"List all available agents I can use."

"We are testing out new numbers. Please use 'from_number' `+18005551234` and dial `+14085551234` assigning my 'agent_555'."

Troubleshooting Retell AI MCP Server with Google ADK

Common issues when connecting Retell AI to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Retell AI + Google ADK FAQ

Common questions about integrating Retell AI MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.