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

Enables MCP-compatible clients to read courses, assignments, announcements, files, and grades from a Canvas LMS instance.

An MCP server for Canvas LMS that enables assistants to read course content, create assignments and pages, set due dates, and post announcements via the Canvas REST API.

Fetch URLs and return clean, LLM-ready markdown with metadata and layered prompt injection defense. Configurable timeouts, word limits, JS rendering, and link extraction. All-in-one MCP server + CLI.

Turns Canvas LMS into a scriptable pipeline and exposes it to AI assistants via MCP for querying courses, grades, assignments, and syncing files using natural language.

Enables instructors to run their Canvas LMS courses through an AI assistant, with 47 tools for reading rosters, drafting and publishing assignments, building modules, grading submissions, posting announcements, and pulling the full gradebook. Writes are enabled by default while deletes stay off, and everything runs with the instructor's own API token inside the courses they already teach, requiring no administrator or app registration.

Enables Claude to interact with Canvas LMS, allowing natural language queries about courses, deadlines, grades, and feedback.

Enables AI assistants to manage Canvas LMS courses, announcements, rubrics, assignments, modules, pages, and student data via the Canvas API.

Provides read-only access to Canvas LMS data including courses, assignments, grades, and deadlines through 23 structured tools.

Read-only FastMCP server for Canvas LMS study data.

Local-first MCP server for Canvas LMS. Stdio transport, no third-party broker, token stays in ~/.canvas.env. Exposes courses, assignments, modules, announcements, grades, planner items, upcoming events, todo list, and bulk file dump as MCP tools.

A local server that enables interaction with Canvas Learning Management System API through Claude Desktop, allowing users to manage courses, access assignments, view announcements, and retrieve course materials.

A web-fetch MCP server for LLM agents that fetches pages with an escalation ladder through different engines, raising FetchBlocked instead of returning blocked content.

Enables AI assistants to access content from authenticated web pages by opening a real browser for manual login and session capture. It saves browser profiles locally so users only need to log in once per service for future automated access.

An MCP server that turns Claude into a full image production studio, enabling creation, editing, resizing, and brand-consistent asset generation across multiple platforms.

An MCP server for Canvas LMS that provides 15 curated tools for everyday student work and a gateway to reach every endpoint your Canvas instance exposes.

Enables LLMs to fetch and extract web content as markdown with browser impersonation to bypass basic bot detection.

Lets AI assistants read a student's Canvas LMS courses, modules, deadlines, announcements and course files through the Canvas REST API, using university single sign-on with MFA instead of an API token, and download lecture slides into per-course folders. All access is read-only and works with any Canvas site, defaulting to Oxford.

Reduces token consumption by 73-87% by cleaning web and API data before it reaches the LLM context window. Supports fetching URLs, searching the web, optimizing JSON, and more.

A dedicated web content fetching and conversion MCP server that provides tools for fetching, converting, and extracting data from web pages.

Enables MCP-capable AI tools such as Claude Code and Codex to operate the locally running XuanShang infinite canvas under one unified ruleset: creating projects and certification groups, uploading and certifying images and reference videos, placing assets on the canvas, building Seedance video nodes, submitting generation, and converting drafts to final videos. Credit-spending actions always require explicit user confirmation, and the plugin never reads or stores API keys.

MCP server for Canvas LMS, providing 115+ tools to read courses, assignments, submissions, rubrics, quizzes; grade, comment, manage course content, and handle Canvas admin workflows from any AI agent.

Enables AI systems to interact with Canvas Learning Management System data, allowing users to access courses, assignments, quizzes, planner items, files, and syllabi through natural language queries.

Enables AI assistants to act as teaching assistants for Canvas LMS, allowing them to browse courses, read student submissions (including PDF/DOCX), grade with rubrics, post announcements, manage modules and pages, and more.

Enables teachers and TAs to use an AI assistant to review Canvas LMS submissions, stage grades, rubric scores, and student-facing feedback locally, and post approved results to SpeedGrader.

Enables programmatic interaction with the Canvas LMS API through the Model Context Protocol. It currently supports listing courses with enrollment type filtering and provides interactive help prompts for tool usage.

This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.

Provides tools to fetch web content in HTML, JSON, text, or Markdown formats via MCP. Supports custom headers, length limits, and start index.

MCP server for web page fetching (converting to Markdown/text with automatic fallback between Tavily and Firecrawl) and web search via Tavily.

A Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampling, with optional local file access.

MCP server that turns DOI, URL, or paper titles into structured Markdown full-text with metadata and assets, enabling AI agents to read beyond abstracts.