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

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Fetches current and three-day weather forecasts for any city using the wttr weather service through a Docker-based MCP server.

Enables interaction with Canvas LMS courses and assignments directly from your LLM, allowing you to retrieve, search, and summarize course information, check due dates, and access assignment details without leaving your AI assistant.

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

A headless browser MCP server that allows AI agents to fetch web content and perform Google searches without API keys, supporting various output formats like Markdown, JSON, HTML, and text.

A read-only Model Context Protocol server that lets AI assistants ask plain-language questions about a student's Canvas LMS data — courses, deadlines, assignments, quizzes, grade breakdowns, files, announcements, discussions, and inbox messages. Every tool issues GET requests only, so nothing can be submitted, posted, deleted, or marked as read.

Enables AI agents to interact with Canvas LMS and Gradescope, allowing users to query courses, assignments, modules, calendar events, and find relevant resources using natural language.

Enables AI agents to search and compare live UK product prices from marketplaces like eBay and Amazon, returning normalised JSON with direct buy links.

An MCP server that enables interaction with the YouTube Data API, allowing users to search videos, get video and channel details, analyze trends, and fetch video transcripts.

Enables students to ask an AI assistant about their Canvas LMS data, including assignments, grades, missing submissions, discussions, and upcoming items, while keeping access read-only and private.

Provides functionality to fetch web content in various formats, including HTML, JSON, plain text, and Markdown.

A Model Context Protocol server that allows LLMs to retrieve and convert web content to markdown without robots.txt restrictions.

Enables MCP clients to read Canvas LMS courses, assignments, deadlines, announcements, pages, and extracted text from course files such as PDFs and slides. It also keeps a daily change log so users can see what is new in their courses.

Enables LLMs to retrieve and process web content by fetching URLs and converting HTML to markdown format. Supports chunked reading of large pages and can access both public websites and local networks.

Enables AI assistants to fetch public data from 120+ sources via natural language and save it locally as Excel, GeoJSON, or KML files.

Enables fetching patents from multiple global sources by patent ID, returning PDF, Markdown, and metadata with automatic caching.

Enables read-only access to explicitly configured Canvas and Ed courses and content through provider-aware MCP tools, with optional Gradescope tools after explicit opt-in. It keeps credentials as keyring or environment references and avoids network requests for disabled providers.

Enables interaction with Canvas courses and assignments through natural language, allowing retrieval, search, and summarization of course and assignment information.

Enables fetching and converting web content into various formats including HTML, JSON, plain text, and Markdown. It supports custom request headers and provides specialized tools for on-demand web data retrieval and transformation.

A Model Context Protocol server that provides web content fetching and conversion capabilities.

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.

Enables fetching and extracting web content as markdown using Firecrawl API, with support for single or multiple concurrent URL fetches and web search capabilities.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

A lightweight MCP server enabling web search and content fetching via TinyFish Free Access API with support for single and burst URL fetch.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Provides web search and page fetching capabilities using Ollama's API.

Enables MCP clients to run web searches and fetch pages, returning structured search results and Markdown page content through two tools.

A set of tools enabling AI agents to interact with Canvas LMS, allowing users to find relevant resources, get course information, and navigate modules through natural language queries.

An MCP server that provides web scraping and Bing search capabilities, supporting both static and dynamic content through Puppeteer. It allows AI assistants to extract page summaries, SEO metadata, and full text with automatic detection for headless browser rendering.