How to integrate Canvas MCP with LlamaIndex

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Introduction

This guide walks you through connecting Canvas to LlamaIndex using the Composio tool router. By the end, you'll have a working Canvas agent that can create a new assignment for my math course, send a message to all students in biology 101, schedule office hours as a calendar event, post a discussion entry in the literature forum through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Canvas account through Composio's Canvas 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:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Canvas
  • Connect LlamaIndex to the Canvas MCP server
  • Build a Canvas-powered agent using LlamaIndex
  • Interact with Canvas through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

What is the Canvas MCP server, and what's possible with it?

The Canvas MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Canvas account. It provides structured and secure access to your courses, assignments, and communications, so your agent can perform actions like creating assignments, posting announcements, sending messages, managing course events, and sharing content on your behalf.

  • Automated assignment management: Have your agent create new assignments or adjust assignment dates and overrides for students, groups, or sections in any of your courses.
  • Course communication and collaboration: Let the agent send messages, start new conversations, or post entries in discussions to keep classes engaged and informed.
  • Calendar and event scheduling: Easily instruct your agent to schedule or update course calendar events and appointment groups, including specific recurrence and blackout dates.
  • Content and notification sharing: Ask your agent to share learning materials, send content to selected users, or create global notifications for everyone in an account.
  • User channel and course creation: Enable your agent to add new communication channels for users or spin up brand new courses with custom configurations, all through secure automation.

Supported Tools & Triggers

Tools
Triggers
Create account notificationCreates a global notification within a canvas account, ensuring `end at` is after `start at` and any specified `notification roles` are valid.
Create appointment groupCreates a new appointment group in canvas for schedulable time slots within specified course or group contexts.
Create an assignmentCreates a new assignment within a specified course in canvas lms.
Create assignment overrideCreates an assignment override to adjust due/unlock/lock dates for an assignment in a course, targeting specific students (requires `title`), a group, or a course section; at least one target (`student ids`, `group id`, or `course section id`) is required.
Create Calendar EventCreates a calendar event with options for recurrence (finite `rrule` series only), section-specific timings, and blackout dates within a specified context.
Create communication channelCreates a new communication channel (e.
Create content shareShares a canvas content item to specified users, if the sender has necessary permissions and receiver ids are valid.
Create conversationUse to send messages in canvas by creating a new conversation or adding to an existing one; an existing conversation with the same recipients (and matching scope/filter, if specified) may be reused unless `force new` is true.
Create a courseCreates a new course in canvas within a specified account, with comprehensive configuration options.
Create discussion entryTool to create a new entry in a canvas discussion topic.
Create discussion topicCreates a new discussion topic in a specified canvas course, allowing comprehensive configuration of its content, type, publication settings, engagement features, and associations.
Create enrollmentEnrolls a user in a canvas course with a specified role and status; `associated user id` is required if `enrollment type` is 'observerenrollment'.
Create FolderCreates a new folder in canvas within a specified context (e.
Create ModuleCreates a new organizational module within a specified canvas lms course, with options for availability, sequencing, and prerequisites.
Create a page for a courseCreates a new wiki page in a specified canvas course, with options for title, html body, editing permissions, publication, and designation as front page (which also requires publication).
Create QuizCreates a new quiz with various settings in a specified existing canvas course; `assignment group id` applies only to graded quiz types.
Create a quiz questionCreates a new question for an existing quiz within a course; if `answers` are provided, their structure must align with `question type`, and any `quiz group id` must be valid for an existing group in the quiz.
Delete appointment groupPermanently deletes an existing appointment group by its id; associated appointments may also be canceled or affected.
Delete an assignmentSoft-deletes a specific assignment within a course, returning the assignment object with its `workflow state` updated to 'deleted'.
Delete a folderPermanently deletes an existing folder specified by its unique id.
Delete quizPermanently deletes the quiz identified by `quiz id` from the course identified by `course id`; this action cannot be undone.
Get current gradesFetches current, aggregated grade data from canvas analytics for a specified account id.
Get term grade dataRetrieves department-level aggregated grade data for a specific academic term within a canvas account.
Edit assignmentUpdates an existing assignment in a canvas course (identified by `course id` and `assignment id`); only attributes explicitly provided in the request are modified.
Edit a quizModifies an existing canvas quiz; only attributes with provided values in the request are updated.
Export contentUse to initiate an asynchronous export of content (e.
Fetch DataFetches a specific category of canvas data (e.
Get Canvas accountsRetrieves all canvas accounts accessible to the authenticated user.
Get all assignmentsRetrieves assignments for a specified canvas course.
Get all usersRetrieves a list of users for a specified canvas `account id` (use 'self' for the current user's root account), supporting filtering, sorting, and pagination.
Get assignmentRetrieves detailed information for a specific assignment within a given course in canvas.
Get Assignment RubricFetches the detailed rubric for a specified assignment within a canvas course; fails if the assignment has no associated rubric.
Get Course ActivityRetrieves daily activity analytics, such as page views and participation events, for a specified canvas course.
Get Current UserRetrieves detailed information about the currently authenticated user from the canvas lms.
Get department-level completed statisticsRetrieves numeric statistics for all completed courses for a specified canvas account id; the account must exist.
Get department level current statisticsFetches a snapshot of current numerical statistics for a canvas account, requiring its valid id.
Get department level completed gradesRetrieves the distribution of final grades (0-100, binned to whole numbers) for all completed courses in a canvas account, where each data point represents one student's final grade in one course.
Get department level term statisticsRetrieves department-level academic term statistics (e.
Get enrollment by IDRetrieves a specific enrollment by its id within a given account.
Get gradebook history daysRetrieves a chronological list of dates with grading activity and the active graders for a specified course.
Get Page for a CourseRetrieves a specific content page (wiki or content page) by its url or numeric id from a specified canvas course.
Get quiz submissionsRetrieves all submissions for a specific quiz within a course; ensure `course id` and `quiz id` are valid and the quiz belongs to the course.
Get report statusRetrieves the status of a previously initiated report in a canvas account, specified by its type and id.
Get a single courseRetrieves detailed information for a specific canvas course using its `course id`, which must be valid, and allows for including additional data fields in the response via the `include` parameter.
Get single submissionRetrieves a specific submission for an assignment made by a particular user within a designated course.
Get submission filesRetrieves files from a student's canvas assignment submission, processing text, binary, and zip files, and providing s3 download urls if s3 integration is active and uploads are successful.
Get user assignment analyticsFetches detailed assignment-level analytics for a specific student in a designated course, including submission details and class performance statistics.
Get user course progressRetrieves the academic progress of a specific user within a given course.
Get user participation analyticsRetrieves page view activity and participation details for a specific student enrolled in a designated course.
Get User ProfileRetrieves profile information for an existing canvas user.
Grade or comment on a submissionUpdates a student's assignment submission with a grade, comment, sticker, or status change; requires `course id`, `assignment id`, `user id`, and at least one update field.
List Accounts for Course AdminsRetrieves canvas accounts visible to the current user due to their course-level administrative roles; no request parameters are needed.
List all foldersRetrieves the first page of folders for a specified canvas course id; this action is scoped to courses only.
List appointment groupsRetrieves a list of canvas appointment groups based on specified filters; any provided `context codes` must be valid and accessible by the user.
List assignment submissionsRetrieves submissions for a specific assignment within a course, optionally including related resources or grouping by student group for group assignments.
List Available ReportsLists available reports (including those that can be or have been generated) for a valid canvas account id.
List calendar events for a userRetrieves calendar events and assignments for a specific user from canvas lms, supporting extensive filtering options detailed in the request schema.
List communication messagesRetrieves communication messages from canvas.
List communication channelsRetrieves a list of communication channels associated with a specific user in canvas.
List content exportsRetrieves a paginated list of content exports from canvas for a specified, existing course.
List coursesRetrieves a list of the current user's courses from canvas, optionally filtered by enrollment type and state.
List Courses for a UserRetrieves a list of courses in canvas for a specified `user id`, requiring observer or admin permissions to view courses for others.
List Course UsersRetrieves a paginated list of users for a given canvas `course id` (which must be an existing course), supporting various filtering, sorting, and data inclusion options.
List Discussion EntriesTool to retrieve paginated discussion entries for a specific discussion topic in a course.
List Discussion TopicsRetrieves a paginated list of discussion topics or announcements for a specified course.
List FilesFetches metadata (id, name, size, type, urls) for all files within a specified canvas course.
List foldersRetrieves a list of immediate sub-folders within the specified `folder id`.
List pages for a courseRetrieves a list of wiki pages associated with a specific, existing course in canvas.
List Quizzes in CourseRetrieves a paginated list of quizzes for a specified, valid canvas course, optionally filtering by a search term in the quiz title.
List sent content sharesRetrieves content shares sent by the specified user to other users or courses within canvas.
List submissionsFetches gradebook history submissions for a specific course, assignment, grader, and date from canvas.
List submissions for multiple assignmentsRetrieves submissions from a canvas course for specified assignments and/or students; the course must be accessible.
List uncollated submission versionsRetrieves a feed of uncollated submission versions from the gradebook history for a course; any provided `assignment id` must be valid for the course, and any `user id` must be for a user enrolled in the course.
List users in accountUse this action to retrieve all users associated with a specific, existing canvas account id.
Reply to discussion entryTool to reply to a discussion entry.
Retrieve enrollment termRetrieves detailed information for a specific enrollment term within a given root account in canvas.
Start a ReportInitiates an asynchronous report generation for a canvas account, using a valid report type for the account; the response confirms initiation and may include progress tracking details.
Translate File ReferenceResolves a file's migration id to its current representation within a specific canvas course.
Update Appointment GroupUpdates an existing canvas appointment group by its id; only provided fields are modified, but `publish` defaults to `false` if omitted.
Update courseUpdates an existing course, specified by its id, with new attributes or triggers a lifecycle event like 'conclude' or 'delete'.
Update course settingsUpdates various settings for an existing course in canvas, identified by `course id`.
Update fileModifies an existing file's name or relocates it to a new parent folder; the target folder, if specified, must be valid and in the file's original context.
Update page for a courseUpdates an existing wiki page in a canvas course; if setting as front page, it must also be or be made published.
Update quiz submission scoresUpdates scores, comments for questions, and/or applies fudge points to a specific quiz submission attempt; the attempt must be completed and referenced by valid, existing course, quiz, and submission ids.
Update User SettingsUpdates a canvas user's preferences for various interface elements and content interaction behaviors.
Upload a course fileUploads a file to an accessible canvas course, optionally to a specific folder (created if a non-existent `parent folder path` is provided) and with defined behavior for duplicate filenames.
Upload submission fileUploads a submission file for an assignment in a canvas course for a specified `user id`; this user must be enrolled, the assignment open for them, and 'masquerade' permissions may be needed if `user id` isn't 'self'.

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 you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Canvas account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Canvas

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Canvas access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called canvas_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["canvas"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Canvas actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Canvas actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, canvas)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Canvas tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Canvas database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Canvas

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Canvas, then start asking questions.

Complete Code

Here's the complete code to get you started with Canvas and LlamaIndex:

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["canvas"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Canvas actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Canvas actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Canvas to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Canvas tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

How to build Canvas MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Canvas MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Canvas MCP with Claude Agent SDK

Google ADK

Google ADK

Use Canvas MCP with Google ADK

LangChain

LangChain

Use Canvas MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Canvas MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Canvas MCP with Mastra AI

CrewAI

CrewAI

Use Canvas MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex 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 Canvas tools.

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

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

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