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How to integrate Remote retrieval MCP with Pydantic AI

Connect Pydantic AI to Remote retrieval MCP. Show all pending laptop return orders, get company info for acme corp, and more using natural language, with authentication handled for you.

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Api Key

Remote retrieval is a logistics automation tool for managing laptop and monitor returns. It streamlines return tracking, saving time and hassle for IT and ops teams.

7 Tools

Introduction

This guide walks you through connecting Remote retrieval to Pydantic AI using the Composio tool router. By the end, you'll have a working Remote retrieval agent that can create return orders, track order details, list pending orders, check device prices, and view company details through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Remote retrieval account through Composio's Remote retrieval MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

For exact tool slugs and parameter tables, see the tool catalog in the Composio docs.

Also integrate Remote retrieval with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

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 Remote retrieval
  • 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 Remote retrieval 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 Remote retrieval MCP server, and what's possible with it?

The Remote retrieval MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Remote retrieval account. It provides structured and secure access to your company’s equipment logistics, so your agent can perform actions like listing equipment return orders, validating API access, and fetching company details on your behalf.

  • Comprehensive order tracking and listing: Ask your agent to retrieve a paginated list of all equipment return orders, with optional filters for status or date to keep tabs on ongoing returns.
  • Company information retrieval: Let your agent pull detailed company information instantly, helping with audits, reporting, or support workflows.
  • API key validation automation: Have your agent confirm that your API key is valid before performing sensitive actions, ensuring secure and authorized access every time.
  • Status-based filtering of return orders: Easily filter and fetch orders by their current status (e.g., pending, completed) to streamline logistics reviews or escalation processes.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
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
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Remote retrieval
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

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
5

Import dependencies

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()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Remote retrieval
  • MCPServerStreamableHTTP connects to the Remote retrieval MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

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 Remote retrieval
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["remote_retrieval"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Remote retrieval 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
remote_retrieval_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[remote_retrieval_mcp],
    instructions=(
        "You are a Remote retrieval assistant. Use Remote retrieval tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Remote retrieval endpoint
  • The agent uses GPT-5 to interpret user commands and perform Remote retrieval operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

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 Remote retrieval.\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()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Remote retrieval API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

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

Complete Code

Here's the complete code to get you started with Remote retrieval and Pydantic AI:

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 Remote retrieval
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["remote_retrieval"],
    )
    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
    remote_retrieval_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[remote_retrieval_mcp],
        instructions=(
            "You are a Remote retrieval assistant. Use Remote retrieval 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 Remote retrieval.\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 Remote retrieval through Composio's Tool Router. With this setup, your agent can perform real Remote retrieval 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 + Remote retrieval for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Remote retrieval action and event your agent gets out of the box.

Create Order

Tool to create IT asset retrieval orders for remote employees.

Get All Orders

Retrieve a page of Remote Retrieval orders, including payment, order, and shipment statuses.

Get Company Details

Retrieve Remote Retrieval company details, such as the company name, contact email, address, and record creation date.

Get Device Prices

Retrieve current pricing for supported devices, including laptops, monitors, tablets, and cell phones.

Get Order Details

Retrieve details for a Remote Retrieval order by order ID.

List Pending Orders

Tool to retrieve list of all pending orders.

RemoteRetrieval: Validate User

Tool to validate the provided API key.

FRAMEWORKS

How to build Remote retrieval MCP Agent with another framework

Claude Code logo

Claude Code

Use Remote retrieval MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Remote retrieval MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Remote retrieval MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Remote retrieval MCP with Claude Agent SDK

Codex logo

Codex

Use Remote retrieval MCP with Codex

OpenClaw logo

OpenClaw

Use Remote retrieval MCP with OpenClaw

Hermes logo

Hermes

Use Remote retrieval MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Remote retrieval MCP with Atomic Agent

Google ADK logo

Google ADK

Use Remote retrieval MCP with Google ADK

LangChain logo

LangChain

Use Remote retrieval MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Remote retrieval MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Remote retrieval MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Remote retrieval MCP with LlamaIndex

CrewAI logo

CrewAI

Use Remote retrieval MCP with CrewAI

AutoGen logo

AutoGen

Use Remote retrieval MCP with AutoGen

FAQ

Frequently asked questions

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