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How to integrate Gagelist MCP with Pydantic AI

Connect Pydantic AI to Gagelist MCP. Add a new calibration record for this gage, generate calibration certificate for equipment id 2345, and more using natural language, with authentication handled for you.

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Gagelist is a calibration management platform with easy APIs and intuitive interfaces. It streamlines equipment tracking and compliance for quality-focused teams.

21 Tools

Introduction

This guide walks you through connecting Gagelist to Pydantic AI using the Composio tool router. By the end, you'll have a working Gagelist agent that can track gages and calibration records, generate calibration certificates, manage manufacturers, and upload attachments to gages through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Gagelist account through Composio's Gagelist 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 Gagelist 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 Gagelist
  • 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 Gagelist 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 Gagelist MCP server, and what's possible with it?

The Gagelist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gagelist account. It provides structured and secure access to your calibration records and asset management workflows, so your agent can perform actions like adding new gages, managing calibration events, generating certificates, and retrieving account information on your behalf.

  • Seamless calibration record management: Direct your agent to add, update, or delete calibration records, keeping your asset compliance up-to-date with minimal manual effort.
  • Automated gage and manufacturer tracking: Have the agent add new gages or manufacturers to your Gagelist inventory, or remove outdated entries as your equipment changes.
  • Instant calibration certificate generation: Let your agent generate official PDF calibration certificates from existing records, streamlining audit and reporting processes.
  • Account insights and status checks: Quickly retrieve your account settings or overall status, giving you a real-time view into your calibration program's health.

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

Add Calibration Record

Creates a new calibration record in GageList to document equipment calibration results.

Add Gage Record

Tool to add a new gage record.

Add Manufacturer

Creates a manufacturer record in GageList for tracking companies that produce gages and measurement instruments.

Authenticate with Gagelist

Tool to obtain a Gagelist API access token.

Delete Calibration Record

Deletes a calibration record by its ID.

Delete Gage Record

Deletes a gage record by its ID.

Delete Manufacturer

Tool to delete a manufacturer by its ID.

Generate Calibration Certificate

Tool to generate a PDF certificate from a calibration record.

Get Account Settings

Tool to get account settings.

Get account status

Tool to retrieve account status.

Get all calibration records

Tool to retrieve a paginated list of calibration records.

Get All Gage Records

Tool to retrieve a paginated list of gage records.

Get All Manufacturers

Tool to retrieve a list of all manufacturers.

Get Attachment

Tool to retrieve an attachment by its ID.

Get Custom Fields

Tool to retrieve custom field definitions.

Get Single Calibration Record

Tool to retrieve details of a single calibration record.

Get Single Gage Record

Retrieves details of a single GageList gage record by its unique ID, including identification, calibration and measurement information, location, responsible user, test templates, and attachment metadata.

Update Account Settings

Updates GageList account settings using a complete settings payload.

Update Custom Field Values

Tool to update custom field values.

Update Manufacturer

Tool to update a manufacturer by its ID.

Upload Attachment To Gage Record

Tool to upload an attachment to a gage record.

FRAMEWORKS

How to build Gagelist MCP Agent with another framework

Claude Code logo

Claude Code

Use Gagelist MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Gagelist MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

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Claude Agent SDK logo

Claude Agent SDK

Use Gagelist MCP with Claude Agent SDK

Codex logo

Codex

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

Use Gagelist MCP with Hermes

Atomic Agent logo

Atomic Agent

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Google ADK logo

Google ADK

Use Gagelist MCP with Google ADK

LangChain logo

LangChain

Use Gagelist MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Gagelist MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Gagelist MCP with Mastra AI

LlamaIndex logo

LlamaIndex

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CrewAI logo

CrewAI

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AutoGen logo

AutoGen

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FAQ

Frequently asked questions

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