# How to integrate Remote retrieval MCP with Pydantic AI

```json
{
  "title": "How to integrate Remote retrieval MCP with Pydantic AI",
  "toolkit": "Remote retrieval",
  "toolkit_slug": "remote_retrieval",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/remote_retrieval/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/remote_retrieval/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:23:41.560Z"
}
```

## 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 show all pending laptop return orders, get company info for acme corp, validate your remote retrieval api key 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.

## Also integrate Remote retrieval with

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `REMOTE_RETRIEVAL_CREATE_ORDER` | Create Order | Tool to create IT asset retrieval orders for remote employees. Use when you need to schedule pickup of laptops, monitors, cell phones, or tablets from employees. Supports both return-to-company and recycle-with-data-destruction workflows. |
| `REMOTE_RETRIEVAL_GET_ALL_ORDERS` | Get All Orders | Tool to retrieve a paginated list of all orders. Use when you need to list orders with optional filters like status or dates. Call after authentication. |
| `REMOTE_RETRIEVAL_GET_COMPANY_DETAILS` | Get Company Details | Tool to retrieve detailed information for a company. Use after confirming a valid company_id. |
| `REMOTE_RETRIEVAL_GET_DEVICE_PRICES` | Get Device Prices | Tool to retrieve real-time pricing data for all supported devices. Use when you need current prices for Laptop, Monitor (17-23 inch), Monitor_27 (24-27 inch), Tablet, or Cell Phone. |
| `REMOTE_RETRIEVAL_GET_ORDER_DETAILS` | Get Order Details | Tool to retrieve specific order details by order ID. Use when you need detailed information about an order including employee info, company info, and shipment status (device_type, send_status, return_status). |
| `REMOTE_RETRIEVAL_LIST_PENDING_ORDERS` | List Pending Orders | Tool to retrieve list of all pending orders. Use when you need to check orders awaiting payment completion. Results are paginated up to 25 per page. |
| `REMOTE_RETRIEVAL_VALIDATE_USER` | RemoteRetrieval: Validate User | Tool to validate the provided API key. Use when you need to confirm the API key's validity. |

## Supported Triggers

None listed.

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

The Remote retrieval MCP server is an implementation of the Model Context Protocol that connects your AI agent to Remote retrieval. It provides structured and secure access so your agent can perform Remote retrieval 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 Remote retrieval
- 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 Remote retrieval
- MCPServerStreamableHTTP connects to the Remote retrieval 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 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
```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")
```

### 6. Initialize the Pydantic AI Agent

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
```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."
    ),
)
```

### 7. Build the chat interface

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
```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()
```

### 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 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.

## How to build Remote retrieval MCP Agent with another framework

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

## Related Toolkits

- [Ashby](https://composio.dev/toolkits/ashby) - Ashby is an applicant tracking system that handles job postings, candidate management, and hiring analytics.
- [Async interview](https://composio.dev/toolkits/async_interview) - Async interview is an on-demand video interview platform for streamlined hiring. Candidates record responses on their schedule, so employers can review anytime.
- [Bamboohr](https://composio.dev/toolkits/bamboohr) - BambooHR is a cloud-based HR management platform for small and mid-sized businesses. It streamlines employee data, HR workflows, and reporting in one easy interface.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Connecteam](https://composio.dev/toolkits/connecteam) - Connecteam is a workforce management platform for deskless teams, streamlining operations, HR, and team communication. It helps businesses save time by automating scheduling, time tracking, and staff engagement tasks.
- [Lever](https://composio.dev/toolkits/lever) - Lever is an applicant tracking system that blends sourcing, CRM, and analytics for recruiting. It helps companies scale hiring with collaborative workflows and actionable insights.
- [Recruitee](https://composio.dev/toolkits/recruitee) - Recruitee is collaborative hiring software that centralizes recruitment tasks for teams. It streamlines sourcing, interviewing, and hiring so you can fill roles faster.
- [Sap successfactors](https://composio.dev/toolkits/sap_successfactors) - Sap successfactors is a cloud-based human capital management suite for HR, payroll, recruiting, and talent management. It helps organizations centralize employee data and streamline the entire employee lifecycle.
- [Talenthr](https://composio.dev/toolkits/talenthr) - TalentHR is an intuitive, all-in-one HR tool for managing employee records, leave, and HR workflows. It streamlines HR operations so businesses can focus on people, not paperwork.
- [Workable](https://composio.dev/toolkits/workable) - Workable is an all-in-one HR software platform that streamlines hiring, employee management, and payroll. It helps teams simplify recruiting, onboarding, and staff operations in one place.
- [Workday](https://composio.dev/toolkits/workday) - Workday is a cloud-based ERP platform for HR, finance, and workforce analytics. It streamlines employee management, payroll, and business operations in a single system.
- [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.
- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.
- [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Remote retrieval MCP?

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

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

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

---
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