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Retell AI MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Create Voice Agent, Get Agent Config, Get Call Details, and more

Built by Vinkius GDPR 11 Tools SDK

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

Use with Your AI Agent

Ask AI about this App Connector for Pydantic AI

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The Retell AI app connector for Pydantic AI is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Retell AI "
            "(11 tools)."
        ),
    )

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

asyncio.run(main())
Retell AI
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IAMAccess control
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DLPData protection
V8 IsolateSandboxed
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<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 Retell AI account to any AI agent and take full control of your conversational voice orchestration through natural conversation. Retell AI provides a premier platform for building human-like voice agents, and this integration allows you to create agents, initiate phone or web calls, and monitor LLM configurations directly from your chat interface.

Pydantic AI validates every Retell AI tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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

  • Agent & Persona Orchestration — List all managed voice agents and retrieve detailed persona metadata, including creating new agents programmatically.
  • Call Lifecycle Management — Initiate and monitor real-time phone or web calls and retrieve detailed call metadata including recordings and transcripts directly from the AI interface.
  • LLM & Brain Control — Access and monitor your Retell LLM configurations to ensure your agents always have the correct logic and knowledge via natural language.
  • Phone Number Intelligence — List available phone numbers to maintain a clear overview of your telephony infrastructure.
  • Operational Monitoring — Track system responses and manage agent settings using simple AI commands to ensure your voice operations are always optimized.

The Retell AI MCP Server exposes 11 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.

All 11 Retell AI tools available for Pydantic AI

When Pydantic AI connects to Retell AI through Vinkius, your AI agent gets direct access to every tool listed below — spanning voice-ai, conversational-ai, telephony, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_voice_agent

Create a new AI voice agent

get_agent_config

Get details for a voice agent

get_call_details

Get details and transcript for a call

get_llm_details

Get metadata for a response engine

get_phone_number

Get details for a specific phone number

list_recent_calls

List call logs and history

list_retell_llms

List internal response engines

list_retell_numbers

List registered phone numbers

list_voice_agents

List all AI voice agents

start_phone_call

Initiate an outbound phone call

start_web_call

Initialize a browser-based call

Connect Retell AI to Pydantic AI via MCP

Follow these steps to wire Retell AI into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 11 tools from Retell AI with type-safe schemas

Why Use Pydantic AI with the Retell AI MCP Server

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

01

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

02

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

03

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

04

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

Retell AI + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Retell AI in Pydantic AI

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

01

"List all my voice agents in Retell AI."

02

"Show me all AI voice agents and their call statistics from the last 7 days."

03

"Create a new outbound phone call using the Sales Qualifier agent to contact a prospect."

Troubleshooting Retell AI MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Retell AI + Pydantic AI FAQ

Common questions about integrating Retell AI MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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