# How to integrate Adrapid MCP with Pydantic AI

```json
{
  "title": "How to integrate Adrapid MCP with Pydantic AI",
  "toolkit": "Adrapid",
  "toolkit_slug": "adrapid",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/adrapid/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/adrapid/framework/pydantic-ai.md",
  "updated_at": "2026-05-06T07:59:18.582Z"
}
```

## Introduction

This guide walks you through connecting Adrapid to Pydantic AI using the Composio tool router. By the end, you'll have a working Adrapid agent that can list all banners with status ready, show your adrapid account api details, get version info for adrapid api through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Adrapid account through Composio's Adrapid MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Adrapid with

- [OpenAI Agents SDK](https://composio.dev/toolkits/adrapid/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/adrapid/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/adrapid/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/adrapid/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/adrapid/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/adrapid/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/adrapid/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/adrapid/framework/cli)
- [Google ADK](https://composio.dev/toolkits/adrapid/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/adrapid/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/adrapid/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/adrapid/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/adrapid/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/adrapid/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 Adrapid
- 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 Adrapid 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 Adrapid MCP server, and what's possible with it?

The Adrapid MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Adrapid account. It provides structured and secure access to your Adrapid digital marketing assets, so your agent can perform actions like retrieving account info, listing banners, and auditing creative assets on your behalf.
- API and account insights: Instantly retrieve up-to-date information about your Adrapid API version and user account for quick troubleshooting or integration checks.
- Automated banner auditing: Have your agent list all existing banners, including their statuses, so you can quickly monitor campaign progress and spot assets ready for launch.
- Filter banners by status: Ask the agent to fetch only banners that meet specific criteria, like those marked 'ready', making campaign tracking simpler and faster.
- Centralized creative asset reporting: Pull a complete overview of all your digital ad visuals in one place, streamlining management and reviews for your team or stakeholders.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ADRAPID_GET_API_INFO` | Get API info | Tool to retrieve api root information. use when you need to discover the api's description and version details. |
| `ADRAPID_GET_SYSTEM_ME` | Get user and API info | Tool to get user account and api information. use when you need to retrieve authenticated user details and api versions. |
| `ADRAPID_LIST_BANNERS` | List Banners | Tool to list all banners and their statuses. use when you need to retrieve banners after creation or to audit existing banners. ensure you apply filters to narrow down results (e.g., status='ready'). |

## Supported Triggers

None listed.

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

The Adrapid MCP server is an implementation of the Model Context Protocol that connects your AI agent to Adrapid. It provides structured and secure access so your agent can perform Adrapid 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 Adrapid
- 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 Adrapid
- MCPServerStreamableHTTP connects to the Adrapid 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 Adrapid 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 Adrapid
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["adrapid"],
    )
    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 Adrapid endpoint
- The agent uses GPT-5 to interpret user commands and perform Adrapid operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
adrapid_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[adrapid_mcp],
    instructions=(
        "You are a Adrapid assistant. Use Adrapid 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
- Adrapid 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 Adrapid.\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 Adrapid
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["adrapid"],
    )
    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
    adrapid_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[adrapid_mcp],
        instructions=(
            "You are a Adrapid assistant. Use Adrapid 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 Adrapid.\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 Adrapid through Composio's Tool Router. With this setup, your agent can perform real Adrapid 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 + Adrapid 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 Adrapid MCP Agent with another framework

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

## Related Toolkits

- [Metaads](https://composio.dev/toolkits/metaads) - Metaads is Meta's official Ads API that lets you manage, analyze, and optimize your Facebook and Instagram ad campaigns. Streamline ad operations and gain deeper insights with robust automation.
- [Adyntel](https://composio.dev/toolkits/adyntel) - Adyntel is an API that retrieves LinkedIn ads for any company using a domain or LinkedIn Page ID. Easily access competitive ad intelligence to power your marketing workflows.
- [Beaconstac](https://composio.dev/toolkits/beaconstac) - Beaconstac is a platform for creating and managing QR codes and proximity beacons. It helps businesses engage customers and track marketing performance with powerful analytics.
- [Campaign cleaner](https://composio.dev/toolkits/campaign_cleaner) - Campaign cleaner is an email campaign optimization tool that boosts compatibility and deliverability across email clients. It helps marketers get better results by cleaning, enhancing, and ensuring high performance for every campaign.
- [Deadline funnel](https://composio.dev/toolkits/deadline_funnel) - Deadline Funnel lets you create personalized deadlines and timers for your marketing campaigns. It helps marketers boost conversions by adding authentic urgency to offers.
- [Google Ads](https://composio.dev/toolkits/googleads) - Google Ads is Google's online advertising platform for creating, managing, and optimizing digital campaigns. It helps businesses reach targeted customers and maximize return on ad spend.
- [Instantly](https://composio.dev/toolkits/instantly) - Instantly is a platform for automating cold email outreach, managing leads, and optimizing deliverability. Get better results from email campaigns with minimal manual effort.
- [Proofly](https://composio.dev/toolkits/proofly) - Proofly is a social proof platform that displays real-time notifications of customer activity on your site. It helps you increase website conversions by building trust and urgency for visitors.
- [Segmetrics](https://composio.dev/toolkits/segmetrics) - Segmetrics is a marketing analytics platform that reveals detailed insights into your customer journeys. It helps businesses optimize marketing strategies with accurate, actionable reporting.
- [Semrush](https://composio.dev/toolkits/semrush) - Semrush is a leading SEO tool suite for keyword research, competitor analysis, and campaign tracking. It empowers marketers to improve search rankings and optimize online visibility.
- [Sendloop](https://composio.dev/toolkits/sendloop) - Sendloop is an all-in-one email marketing platform built for SaaS, e-commerce, and small businesses. It makes it easy to send campaigns, manage lists, and track results—all in one place.
- [Sidetracker](https://composio.dev/toolkits/sidetracker) - Sidetracker is a marketing analytics platform that tracks expenses, sales funnels, and customer journeys. It helps optimize marketing spend and visualize campaign performance from start to finish.
- [Stannp](https://composio.dev/toolkits/stannp) - Stannp is an API-driven direct mail platform for sending postcards and letters programmatically. It lets you automate physical mail delivery—no manual printing or mailing required.
- [Tapfiliate](https://composio.dev/toolkits/tapfiliate) - Tapfiliate is an affiliate and referral tracking platform for businesses. It helps companies efficiently manage, track, and grow their affiliate programs.
- [Tpscheck](https://composio.dev/toolkits/tpscheck) - Tpscheck is a real-time service for verifying UK phone numbers against TPS and CTPS registers. It helps prevent unwanted marketing calls and ensures compliance with UK telemarketing laws.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options.
- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide.

## Frequently Asked Questions

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

With a standalone Adrapid MCP server, the agents and LLMs can only access a fixed set of Adrapid tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Adrapid 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 Adrapid tools.

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

Yes, absolutely. You can configure which Adrapid 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 Adrapid data and credentials are handled as safely as possible.

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