How to integrate Codereadr MCP with Pydantic AI

This guide walks you through connecting Codereadr to Pydantic AI using the Composio tool router. By the end, you'll have a working Codereadr agent that can create a new barcode scanning service, configure survey questions after each scan, enable kiosk mode for unattended device through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Codereadr account through Composio's Codereadr MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Codereadr is a mobile platform for barcode scanning and data collection. It helps businesses securely capture, validate, and report field data with ease.

16 Tools

Introduction

This guide walks you through connecting Codereadr to Pydantic AI using the Composio tool router. By the end, you'll have a working Codereadr agent that can create a new barcode scanning service, configure survey questions after each scan, enable kiosk mode for unattended device through natural language commands.

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

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

Also integrate Codereadr with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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

The Codereadr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Codereadr account. It provides structured and secure access to your data collection and barcode scanning workflows, so your agent can create services, configure scan workflows, manage databases, and automate data collection processes for you.

  • Automated service and workflow setup: Let your agent create new CodeREADr services and configure custom workflows for scanning, picking, delivery, and receiving tasks.
  • Custom data collection form creation: Easily set up or modify data capture forms by adding or deleting custom questions after each scan.
  • Real-time scan integration: Configure Direct Scan URLs, postback endpoints, or Google Sheets connectors to forward scan results instantly to your desired platforms.
  • Device and database management: Direct your agent to delete devices or entire databases when they are no longer needed, streamlining your data environment.
  • Kiosk and unattended scanning configuration: Enable and fine-tune Kiosk Mode for unattended or dedicated scanning stations to support high-volume operations.

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 Codereadr
  • 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 Codereadr
  • MCPServerStreamableHTTP connects to the Codereadr 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 Codereadr
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["codereadr"],
    )
    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 Codereadr 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
codereadr_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[codereadr_mcp],
    instructions=(
        "You are a Codereadr assistant. Use Codereadr tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Codereadr endpoint
  • The agent uses GPT-5 to interpret user commands and perform Codereadr 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 Codereadr.\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
  • Codereadr 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 Codereadr 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 Codereadr
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["codereadr"],
    )
    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
    codereadr_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[codereadr_mcp],
        instructions=(
            "You are a Codereadr assistant. Use Codereadr 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 Codereadr.\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 Codereadr through Composio's Tool Router. With this setup, your agent can perform real Codereadr 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 + Codereadr 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 Codereadr action and event your agent gets out of the box.

Collect Data With Questions

Create and attach custom questions to a CodeREADr service for data collection after scans.

Configure CodeREADr Connector

Helper to guide configuring the CodeREADr Connector for Google Sheets.

Create CodeREADr Service

Creates a new CodeREADr service (barcode scanning workflow configuration).

Delete CodeREADr Database

Delete a CodeREADr validation database by its ID.

Delete Device

Tool to delete a device from CodeREADr.

Delete Custom Question

Permanently deletes one or more custom questions from your CodeREADr account.

Delete CodeREADr Service

Delete a CodeREADr service by its numeric ID.

Delete CodeREADr User

Deletes an existing user account from CodeREADr.

Generate Scan Link

Generates a CodeREADr scan link URI that opens the CodeREADr mobile app with a pre-filled scan value.

List Supported Barcode Types

Lists barcode symbologies supported by CodeREADr for scanning.

Retrieve CodeREADr Databases

Retrieves all validation databases configured in your CodeREADr account.

Retrieve Devices

Retrieve a list of devices registered to your CodeREADr account.

Retrieve Scan Records

Retrieve scan records from your CodeREADr account.

Retrieve CodeREADr Services

Retrieve configured services from your CodeREADr account.

Update CodeREADr Question

Add answer options to an existing CodeREADr question.

Update CodeREADr Service

Update an existing CodeREADr service configuration.

FRAMEWORKS

How to build Codereadr MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Codereadr MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Codereadr MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Codereadr MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Codereadr MCP with Claude Cowork

Codex logo

Codex

Use Codereadr MCP with Codex

OpenClaw logo

OpenClaw

Use Codereadr MCP with OpenClaw

Hermes logo

Hermes

Use Codereadr MCP with Hermes

CLI logo

CLI

Use Codereadr MCP with CLI

Google ADK logo

Google ADK

Use Codereadr MCP with Google ADK

LangChain logo

LangChain

Use Codereadr MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Codereadr MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Codereadr MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Codereadr MCP with LlamaIndex

CrewAI logo

CrewAI

Use Codereadr MCP with CrewAI

FAQ

Frequently asked questions

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

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 Codereadr tools.

Yes, absolutely. You can configure which Codereadr 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.

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 Codereadr data and credentials are handled as safely as possible.

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