How to integrate D2lbrightspace MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting D2lbrightspace to the OpenAI Agents SDK 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quiz for my math course, add a new user to the spring semester, copy an instructor role for a new department, delete an outdated course template from the system through natural language commands.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 OpenAI Agents SDK 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:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for D2lbrightspace
  • Configure an AI agent that can use D2lbrightspace as a tool
  • Run a live chat session where you can ask the agent to perform D2lbrightspace operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live D2lbrightspace project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like D2lbrightspace.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a D2lbrightspace Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["d2lbrightspace"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only d2lbrightspace.
  • The router checks the user's D2lbrightspace connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access D2lbrightspace.
  • This approach keeps things lightweight and lets the agent request D2lbrightspace tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access D2lbrightspace. "
        "Help users perform D2lbrightspace operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access D2lbrightspace and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute D2lbrightspace operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize D2lbrightspace.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with D2lbrightspace and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["d2lbrightspace"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access D2lbrightspace. "
        "Help users perform D2lbrightspace operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating D2lbrightspace MCP with OpenAI Agents SDK to build a functional AI agent that can interact with D2lbrightspace.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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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