# How to integrate Callerapi MCP with Pydantic AI

```json
{
  "title": "How to integrate Callerapi MCP with Pydantic AI",
  "toolkit": "Callerapi",
  "toolkit_slug": "callerapi",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/callerapi/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/callerapi/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:04:49.906Z"
}
```

## Introduction

This guide walks you through connecting Callerapi to Pydantic AI using the Composio tool router. By the end, you'll have a working Callerapi agent that can check if this phone number is flagged as spam, retrieve carrier and business info for a caller, show your callerapi credit usage this month through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Callerapi account through Composio's Callerapi MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Callerapi with

- [OpenAI Agents SDK](https://composio.dev/toolkits/callerapi/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/callerapi/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/callerapi/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/callerapi/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/callerapi/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/callerapi/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/callerapi/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/callerapi/framework/cli)
- [Google ADK](https://composio.dev/toolkits/callerapi/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/callerapi/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/callerapi/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/callerapi/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/callerapi/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/callerapi/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- How to set up your Composio API key and User ID
- How to create a Composio Tool Router session for Callerapi
- How to attach an MCP Server to a Pydantic AI agent
- How to stream responses and maintain chat history
- How to build a simple REPL-style chat interface to test your Callerapi workflows

## What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.
Key features include:
- Type Safety: Built on Pydantic for automatic data validation
- MCP Support: Native support for Model Context Protocol servers
- Streaming: Built-in support for streaming responses
- Async First: Designed for async/await patterns

## What is the Callerapi MCP server, and what's possible with it?

The Callerapi MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Callerapi account. It provides structured and secure access to caller identification and reputation data, so your agent can perform actions like verifying phone numbers, checking caller reputation, retrieving business and carrier details, and monitoring account usage on your behalf.
- Detailed phone number lookup: Instantly retrieve information about any phone number, including reputation, business association, carrier, and FTC complaints.
- Reputation and fraud assessment: Empower your agent to check if a phone number might be flagged for spam, robocalls, or fraud, helping you screen and validate callers.
- Business and carrier identification: Have your agent fetch in-depth business and carrier details for a given number to strengthen trust and context in communications.
- HLR (Home Location Register) checks: Enable your agent to request HLR data for deeper carrier and number status insights, including ported or roaming status.
- Account usage monitoring: Let your agent access your Callerapi user profile to monitor credit usage, monthly allocations, and remaining balance, keeping you informed about your API consumption.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CALLERAPI_DISPATCH_REPORTS_MANUALLY` | Dispatch Reports Manually | Tool to manually trigger today's spam reports webhook delivery for enterprise clients. Use when an immediate webhook dispatch of spam complaint reports is needed. This endpoint is restricted to enterprise accounts only. |
| `CALLERAPI_GET_PHONE_NUMBER_INFORMATION` | Get Phone Number Information | Tool to retrieve detailed information about a specific phone number, including reputation, business and carrier details, and FTC complaints. Use when the number is in E.164 format and set hlr=true to include HLR data (adds 1-3 seconds to response). |
| `CALLERAPI_GET_USER_INFORMATION` | Get User Information | Tool to retrieve information about the authenticated user, including email and credit usage details. Use after authentication to fetch current credits spent, monthly allocation, and credits left. |
| `CALLERAPI_LIST_WEBHOOK_SUBSCRIPTIONS` | List Webhook Subscriptions | Tool to list all webhook subscriptions for daily spam reports. Enterprise clients only. Use to retrieve all configured webhook endpoints that receive spam complaint notifications. |
| `CALLERAPI_SUBSCRIBE_DAILY_REPORTS` | Subscribe to Daily Spam Reports | Tool to subscribe to daily spam report webhooks for enterprise clients. Instead of polling, receive webhook deliveries with spam complaint data daily. Use when you want to set up automated daily reports for spam complaints. |
| `CALLERAPI_TEST_WEBHOOK` | Test Webhook | Tool to send a sample webhook payload to test your webhook endpoint integration. Use to validate webhook signature verification and endpoint configuration. Enterprise clients only. |
| `CALLERAPI_UNSUBSCRIBE_DAILY_REPORTS` | Unsubscribe from Daily Reports | Tool to unsubscribe from daily spam report webhooks. Use when you need to stop receiving daily reports at a specific webhook URL. Enterprise clients only. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Callerapi MCP server is an implementation of the Model Context Protocol that connects your AI agent to Callerapi. It provides structured and secure access so your agent can perform Callerapi operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Python 3.9 or higher
- A Composio account with an active API key
- Basic familiarity with Python and async programming

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install the required libraries.
What's happening:
- composio connects your agent to external SaaS tools like Callerapi
- pydantic-ai lets you create structured AI agents with tool support
- python-dotenv loads your environment variables securely from a .env file
```bash
pip install composio pydantic-ai python-dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your agent to Composio's API
- USER_ID associates your session with your account for secure tool access
- OPENAI_API_KEY to access OpenAI LLMs
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key
```

### 4. Import dependencies

What's happening:
- We load environment variables and import required modules
- Composio manages connections to Callerapi
- MCPServerStreamableHTTP connects to the Callerapi MCP server endpoint
- Agent from Pydantic AI lets you define and run the AI assistant
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
```

### 5. Create a Tool Router Session

What's happening:
- We're creating a Tool Router session that gives your agent access to Callerapi tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
```python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Callerapi
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["callerapi"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
```

### 6. Initialize the Pydantic AI Agent

What's happening:
- The MCP client connects to the Callerapi endpoint
- The agent uses GPT-5 to interpret user commands and perform Callerapi operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
callerapi_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[callerapi_mcp],
    instructions=(
        "You are a Callerapi assistant. Use Callerapi tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
```

### 7. Build the chat interface

What's happening:
- The agent reads input from the terminal and streams its response
- Callerapi API calls happen automatically under the hood
- The model keeps conversation history to maintain context across turns
```python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Callerapi.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
```

### 8. Run the application

What's happening:
- The asyncio loop launches the agent and keeps it running until you exit
```python
if __name__ == "__main__":
    asyncio.run(main())
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Callerapi
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["callerapi"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    callerapi_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[callerapi_mcp],
        instructions=(
            "You are a Callerapi assistant. Use Callerapi tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Callerapi.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You've built a Pydantic AI agent that can interact with Callerapi through Composio's Tool Router. With this setup, your agent can perform real Callerapi actions through natural language.
You can extend this further by:
- Adding other toolkits like Gmail, HubSpot, or Salesforce
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Callerapi for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

## How to build Callerapi MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/callerapi/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/callerapi/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/callerapi/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/callerapi/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/callerapi/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/callerapi/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/callerapi/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/callerapi/framework/cli)
- [Google ADK](https://composio.dev/toolkits/callerapi/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/callerapi/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/callerapi/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/callerapi/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/callerapi/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/callerapi/framework/crew-ai)

## Related Toolkits

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- [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates.
- [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates.
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- [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates.
- [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
- [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.
- [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support.
- [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach.
- [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback.
- [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Callerapi MCP?

With a standalone Callerapi MCP server, the agents and LLMs can only access a fixed set of Callerapi tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Callerapi and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Pydantic AI?

Yes, you can. Pydantic AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Callerapi tools.

### Can I manage the permissions and scopes for Callerapi while using Tool Router?

Yes, absolutely. You can configure which Callerapi scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Callerapi data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
