How to integrate D2lbrightspace MCP with Pydantic AI

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Introduction

This guide walks you through connecting D2lbrightspace to Pydantic AI using the Composio tool router. By the end, you'll have a working D2lbrightspace agent that can create a new quiz for my math course, add a new user to the spring semester, copy an instructor role for a new department, delete an outdated course template from the system through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a D2lbrightspace account through Composio's D2lbrightspace MCP server.

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

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 D2lbrightspace
  • 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 D2lbrightspace 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 D2lbrightspace MCP server, and what's possible with it?

The D2lbrightspace MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your D2L Brightspace account. It provides structured and secure access to your LMS, so your agent can perform actions like creating courses, managing quizzes, handling user enrollment, and automating gradebook operations on your behalf.

  • Automated course creation and management: Instantly create new courses, course offerings, or templates, and streamline updates or deletions without manual intervention.
  • Quiz and assessment automation: Let your agent set up new quizzes, organize quiz categories, and configure assessment parameters to enhance the learning experience.
  • Gradebook and feedback management: Effortlessly create, modify, or delete grade objects to keep your course grading up to date and provide prompt feedback to learners.
  • User enrollment and management: Create new user accounts, manage user roles, and handle enrollment or impersonation tasks to simplify onboarding and administration.
  • Role and permissions control: Copy existing roles, adjust specific permissions, and fine-tune access for different user groups—all directly through your agent.

Supported Tools & Triggers

Tools
Copy RoleCreates a new role copied from an existing role in d2l brightspace.
Create Course OfferingCreates a new course offering in d2l brightspace.
Create Course TemplateCreates a new course template in d2l brightspace.
Create Grade ObjectCreates a new grade object for a particular org unit.
Create QuizCreates a new quiz in d2l brightspace.
Create Quiz CategoryCreates a new quiz category in d2l brightspace.
Create UserCreates a new user entity in d2l brightspace.
Delete Course TemplateDeletes a course template from d2l brightspace.
Delete CourseDeletes a course offering from d2l brightspace.
Delete Grade ObjectDeletes a specific grade object from an org unit.
Delete QuizDeletes a quiz from d2l brightspace.
Delete Quiz CategoryDeletes a quiz category from d2l brightspace.
Delete UserDeletes a user entity from d2l brightspace.
Delete User DemographicsDeletes one or more of a particular user's associated demographics entries.
Get Course OfferingRetrieves a specific course offering from d2l brightspace.
Get Course TemplateRetrieves a course template from d2l brightspace.
Get Course SchemaRetrieves the list of parent org unit type constraints for course offerings.
Get Course Template SchemaRetrieves the list of parent org unit type constraints for course offerings built on this template.
Get Current User InformationRetrieves the current user context's user information from d2l brightspace.
Get Enrolled RolesRetrieves a list of all enrolled user roles the calling user can view in an org unit.
Get Grade AccessRetrieves a list of users with access to a specified grade.
Get Grade ObjectRetrieves a specific grade object for a particular org unit.
Get Grade ObjectsRetrieves all current grade objects for a particular org unit.
Get Grade SetupRetrieves the grades configuration for an org unit.
Get Grade StatisticsRetrieves statistics for a specified grade item.
Get Org Unit DemographicsRetrieves all demographics entries for users enrolled in a particular org unit.
Get QuizRetrieves a specific quiz from an org unit.
Get Quiz AccessRetrieves a list of users with access to a specified quiz.
Get Quiz AttemptRetrieves a specific quiz attempt.
Get Quiz AttemptsRetrieves a list of attempts for a quiz.
Get Quiz CategoriesRetrieves all quiz categories belonging to an org unit.
Get Quiz CategoryRetrieves a specific quiz category from an org unit.
Get Quiz QuestionsRetrieves all questions in a quiz.
Get QuizzesRetrieves all quizzes belonging to an org unit.
Get Role by IDRetrieves a particular user role from d2l brightspace by its id.
Get RolesRetrieves a list of all known user roles in d2l brightspace.
Get User by IDRetrieves data for a particular user from d2l brightspace.
Get UsersRetrieves data for one or more users from d2l brightspace.
Update Course OfferingUpdates an existing course offering in d2l brightspace.
Update Course TemplateUpdates an existing course template in d2l brightspace.
Update Grade ObjectUpdates a specific grade object.
Update Grade SetupUpdates the grades configuration for an org unit.
Update QuizUpdates an existing quiz in d2l brightspace.
Update Quiz CategoryUpdates an existing quiz category in d2l brightspace.
Update UserUpdates an existing user entity in d2l brightspace.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

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

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.

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 D2lbrightspace
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

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

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 D2lbrightspace
  • MCPServerStreamableHTTP connects to the D2lbrightspace MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

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 D2lbrightspace
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["d2lbrightspace"],
    )
    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 D2lbrightspace 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

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
d2lbrightspace_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[d2lbrightspace_mcp],
    instructions=(
        "You are a D2lbrightspace assistant. Use D2lbrightspace tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the D2lbrightspace endpoint
  • The agent uses GPT-5 to interpret user commands and perform D2lbrightspace operations
  • The instructions field defines the agent's role and behavior

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 D2lbrightspace.\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
  • D2lbrightspace API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

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 D2lbrightspace 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 D2lbrightspace
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["d2lbrightspace"],
    )
    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
    d2lbrightspace_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[d2lbrightspace_mcp],
        instructions=(
            "You are a D2lbrightspace assistant. Use D2lbrightspace 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 D2lbrightspace.\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 D2lbrightspace through Composio's Tool Router. With this setup, your agent can perform real D2lbrightspace 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 + D2lbrightspace 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 D2lbrightspace MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use D2lbrightspace MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use D2lbrightspace MCP with Claude Agent SDK

Google ADK

Google ADK

Use D2lbrightspace MCP with Google ADK

LangChain

LangChain

Use D2lbrightspace MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use D2lbrightspace MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use D2lbrightspace MCP with Mastra AI

LlamaIndex

LlamaIndex

Use D2lbrightspace MCP with LlamaIndex

CrewAI

CrewAI

Use D2lbrightspace MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and D2lbrightspace MCP?

With a standalone D2lbrightspace MCP server, the agents and LLMs can only access a fixed set of D2lbrightspace tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from D2lbrightspace 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 D2lbrightspace tools.

Can I manage the permissions and scopes for D2lbrightspace while using Tool Router?

Yes, absolutely. You can configure which D2lbrightspace 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 D2lbrightspace data and credentials are handled as safely as possible.

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Context
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Letta
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HubSpot
Agent.ai
Altera
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Rolai

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