"How to access resources from a Canvas course" matching MCP servers:

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

Enables MCP clients to operate a RunningHub infinite canvas through a local bridge and Chrome extension using the current logged-in session: reading nodes and prompts, cloning templates, laying out and connecting nodes, uploading images/audio/video, submitting generation, and archiving outputs. Supports both the international (www.runninghub.ai / rhtv.runninghub.ai) and China sites, with dry-run previews and revision-checked edits.

Local MCP server that enables downloading papers from arXiv, OpenReview, INFORMS, and Wiley by reusing your Chrome login state.

Enables browsing and collecting course materials from Brightspace through Chrome DevTools Protocol, allowing snapshotting, downloading media, and automating page navigation.

A local MCP server that enables Codex to inspect and interact with Chrome tabs through the Chrome DevTools Protocol, primarily for collecting authorized Brightspace course materials into local folders.

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Enables converting any webpage to clean LLM-ready markdown, with extraction, article, and news modes, using a real browser with anti-bot handling.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Converts X (Twitter) posts into JSON, PDF, PNG, Markdown, or Slack/Discord messages using public endpoints, no API key or login required.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables AI agents to convert HTML content into clean Markdown, stripping scripts and styles while preserving headings, links, lists, and images, with pay-per-call x402 micropayments and no API keys.

Provides web access tools (fetch, search, sitemap crawl) through String AI's API, automatically handling anti-bot bypass, CAPTCHA, and JavaScript rendering.

Enables AI assistants to search for vehicles, manage reservations, and access Enterprise Plus loyalty account information through headless browser automation on enterprise.com. It supports the complete car rental workflow including vehicle searching, booking, modifications, and points balance checks.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Converts any webpage URL to clean, well-formed Markdown with title and H1 preservation, URL validation, and graceful fallbacks. One of 16 single-purpose servers in an open-source monorepo with full CI/CD to PyPI.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.