How do I find my Aircall API ID and Token?

Log in to your Aircall Dashboard, navigate to **Integrations & API** > **API keys**, and create a new key. You will see both the `api_id` and `api_token` there.

Can I listen to call recordings via the agent?

The `get_call_details` tool provides the URL to the call recording if available. Your agent can retrieve this metadata, and you can access the link to listen to the audio.

Does this support checking user availability?

Yes! Use the `get_user_details` tool. It returns the current availability status (Available, Busy, or Offline) for any team member in your account.

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

Name: Aircall
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 Aircall 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 Aircall "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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* 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 Aircall MCP Server

Connect your Aircall account to your AI agent to unlock professional voice orchestration and communication management. From auditing call logs and recordings to managing shared contacts and monitoring team availability, your agent handles your phone system through natural conversation.

Pydantic AI validates every Aircall 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

Call Orchestration — List and retrieve details for calls, including recordings, durations, and participant metadata
Contact Management — Create, update, and search for shared or private contacts within your Aircall account
Team Oversight — List users and teams to check availability statuses and departmental assignments
Number Auditing — Retrieve details for your Aircall phone numbers, including their technical configurations
Communication Insights — Quickly identify call trends or lookup contact history directly from your chat interface

The Aircall 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 Aircall to Pydantic AI via MCP

Follow these steps to integrate the Aircall 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 Aircall with type-safe schemas

Why Use Pydantic AI with the Aircall MCP Server

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

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

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

Aircall + Pydantic AI Use Cases

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

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

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

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

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

Aircall MCP Tools for Pydantic AI (10)

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

create_contact

Add a new contact

get_call_details

Get call technical details

get_number_details

Get number configuration

get_user_details

Get user availability

list_calls

List call logs

list_contacts

List Aircall contacts

list_numbers

List phone numbers

list_teams

List Aircall teams

list_users

List team members

search_contacts

Search contacts by phone

Example Prompts for Aircall in Pydantic AI

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

"List the last 10 calls made by my team."

"Search for a contact with name 'John Doe'."

"Check if user 'Jane Smith' is currently available for calls."

Troubleshooting Aircall MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Aircall + Pydantic AI FAQ

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