"How to fetch assignments from Canvas" matching MCP servers:

MCP server that connects AI assistants to Instructure Canvas LMS, enabling teachers and administrators to manage courses, assignments, grades, and more through natural language.

Connects Claude to Canvas LMS for managing coursework through natural language, including assignments, discussions, submissions, and course browsing.

Connects Canvas LMS to Claude Desktop, enabling natural-language queries about courses, assignments, grades, and more.

TypeScript MCP server for Canvas LMS that exposes Canvas API workflows for courses, assignments, submissions, modules, pages, discussions, announcements, files, users, enrollments, conversations, calendar, and utility endpoints.

Enables AI assistants to interact with Canvas LMS through 25 comprehensive tools. Supports course management, assignments, grades, messaging, calendar events, and file access through natural language.

Connects Claude Desktop to Canvas LMS to monitor academic activities like assignments, announcements, and upcoming deadlines. It enables users to track courses and pending tasks through a unified interface using the Canvas REST API.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Enables AI clients like Claude to read and manage Microsoft To Do task lists and tasks via the Microsoft Graph API, running locally over stdio with secure token storage.

Enables to manage to-do items through natural language, with tools for creating, reading, updating, and deleting tasks.

Enables coding agents to manage Microsoft To Do lists and tasks through Microsoft Graph, with optional support for checklist items, linked resources, attachments, and delta synchronization.

A Model Context Protocol (MCP) server that enables AI assistants like Claude and Cursor to interact with Microsoft To Do via the Microsoft Graph API.

Enables an AI assistant to manage a simple to-do list stored in a local JSON file, with tools to add, list, get, complete, and delete tasks, plus a read-only pending tasks resource.

MCP server for Microsoft To Do via Microsoft Graph. MSAL device code flow, no client secret needed.

Lightweight project management for teams and AI agents.

Enables AI agents to manage Kanban boards, cards, sessions, and automations through a unified MCP interface with real-time updates, supporting delegation, agent sessions, and human-in-the-loop interactions.

A read-only MCP server for fortyTimer, exposing tools to fetch time balances, time entries, project times, and leave requests.

MCP server for managing AIProject tasks and projects, providing CRUD operations for projects, tasks, and assignments with API key authentication.

Enables VS Code Copilot to interact with your Jira instance—Cloud, Server, or Data Center—through natural language for issue search, creation, updates, comments, transitions, assignments, project listing, and user profile lookup.

Enables AI assistants to interact with Jira by executing commands through the Atlassian CLI. It supports searching issues with JQL, managing comments, updating statuses, and handling issue assignments through natural language.

Enables MCP clients to fetch complete PingCode work item details (including description, comments, activities, and attachment metadata) via a read-only stdio server, with support for multiple authentication methods.