# How to integrate Linguapop MCP with Pydantic AI

```json
{
  "title": "How to integrate Linguapop MCP with Pydantic AI",
  "toolkit": "Linguapop",
  "toolkit_slug": "linguapop",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/linguapop/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/linguapop/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:17:38.101Z"
}
```

## Introduction

This guide walks you through connecting Linguapop to Pydantic AI using the Composio tool router. By the end, you'll have a working Linguapop agent that can show all languages available for testing, check if italian is supported for placement, list every language students can choose through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Linguapop account through Composio's Linguapop MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Linguapop with

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

The Linguapop MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Linguapop account. It provides structured and secure access to language placement test data, so your agent can retrieve supported languages, prepare test workflows, and streamline test administration on your behalf.
- Retrieve available test languages: Instantly fetch the list of languages supported by Linguapop to ensure accurate placement and test planning.
- Validate language support prior to testing: Have your agent confirm whether a specific language is available for placement tests before assigning or scheduling exams.
- Automate test setup workflows: Let your agent check supported languages and prepare the necessary resources for candidates or classes without manual intervention.
- Dynamic multilingual experience management: Seamlessly adapt testing options for students or staff based on real-time language availability from Linguapop.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `LINGUAPOP_FETCH_AVAILABLE_LANGUAGES` | Fetch Available Languages | Tool to retrieve the list of available languages. Use when you need to verify supported languages before starting a placement test. |

## Supported Triggers

None listed.

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

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

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

## Related Toolkits

- [Canvas](https://composio.dev/toolkits/canvas) - Canvas is a learning management system for online courses, assignments, grading, and collaboration. It's trusted by educators and students to streamline virtual classrooms and enhance digital learning.
- [Accredible certificates](https://composio.dev/toolkits/accredible_certificates) - Accredible Certificates is a platform for creating and managing digital certificates, badges, and blockchain credentials. It streamlines issuing, tracking, and verifying professional achievements for organizations of any size.
- [Api bible](https://composio.dev/toolkits/api_bible) - API.Bible is a developer platform for Scripture content and passage search. Easily integrate Bible verses and translations into your apps or chatbots.
- [Blackboard](https://composio.dev/toolkits/blackboard) - Blackboard is a digital learning platform for higher education and schools, offering tools to manage courses, track engagement, and deliver interactive content. It helps institutions improve student outcomes through actionable analytics and in-app guidance.
- [Certifier](https://composio.dev/toolkits/certifier) - Certifier is a platform for creating, managing, and issuing digital certificates and credentials. Organizations use it to automate and secure the entire credentialing process.
- [Classmarker](https://composio.dev/toolkits/classmarker) - ClassMarker is a professional online quiz maker for business and education. It provides instant grading, flexible test design, and in-depth reporting.
- [Coassemble](https://composio.dev/toolkits/coassemble) - Coassemble is a flexible platform for building, managing, and delivering online training courses. It helps teams streamline onboarding, upskilling, and ongoing learning for employees or partners.
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- [Dictionary api](https://composio.dev/toolkits/dictionary_api) - Dictionary api is the Merriam-Webster API providing rich dictionary and thesaurus data for developers. Instantly access definitions, synonyms, etymologies, and audio pronunciations in your apps.
- [Google Classroom](https://composio.dev/toolkits/google_classroom) - Google Classroom is a free web service for educators and students to manage assignments and communication. It streamlines classroom collaboration and grading, making teaching simpler and more connected.
- [Lessonspace](https://composio.dev/toolkits/lessonspace) - Lessonspace is an online collaborative classroom platform offering video, whiteboards, and real-time interaction for educators and students. It streamlines remote teaching with integrated tools for engagement and communication.
- [Memberspot](https://composio.dev/toolkits/memberspot) - Memberspot is an online course and video-hosting platform for business learning. It helps teams manage, deliver, and track knowledge efficiently.
- [Membervault](https://composio.dev/toolkits/membervault) - Membervault is a platform for hosting courses, memberships, and digital products in one place. It helps you build stronger relationships with your audience by centralizing digital offers and customer engagement.
- [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.

## Frequently Asked Questions

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

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

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

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

---
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