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

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Enables agents to discover how a website serves its data, verify sources with evidence, export OpenAPI 3.1, and generate tested TypeScript or Python clients.

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 fully working MCP server built from scratch in plain Node.js, implementing tools, resources, prompts, notifications, and sampling according to the MCP specification, designed to connect to Claude Desktop or any MCP client.

A local MCP server that lets coding agents draw and modify diagrams on a canvas, connect shapes into flows, and respond to comments left on the canvas, persisting work as diagram files inside named projects.

Provides MCP tools and a local HTTP API to incrementally synchronize Codex conversations into a structured thinking canvas with AI-automated picking and manual override.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Relays a locally running Microsoft Canvas Authoring MCP server to remote MCP clients, enabling natural language editing and control of Power Apps Canvas apps through a WebSocket bridge.

Enables AI agents to manage routes on the Design Canvas infinite canvas app, including adding, removing, listing routes, and capturing screenshots of the canvas.

Provides read-only access to Canvas LMS for students to retrieve courses, assignments, grades, files, discussions, and planner items. Includes optional NotebookLM integration for uploading course content to AI-powered study notebooks.

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.

Lets stdio-only MCP clients such as Claude Desktop, Cursor, and local agents reach a streamable-http MCP endpoint by transparently relaying line-delimited JSON-RPC over stdin/stdout, passing upstream HTTP errors through unchanged and supporting token-based authentication.

Enables AI agents to capture coding sessions onto a shared transit map of threads and records, then list, read, fork, merge and log entries on it. It also exposes running sessions and per-thread goals and to-dos, so a new session can catch up on prior work across projects instead of rereading old chats.

A powerful and flexible package designed to simplify HTTP/HTTPS requests by automatically applying authentication credentials based on configurable rules. It acts as a seamless proxy for your fetch calls, finding the correct authentication method for a given URL, and attaching the necessary headers or parameters.

A Model Context Protocol (MCP) server for Canvas Medical API/SDK development assistance, providing streamlined access to Canvas Medical documentation and AI-powered development tools.

MCP server for creating interactive terminal canvases (calendar, document, flight) in AI coding assistants. Supports multiple TUI frameworks and integrates with tmux.

Enables coding agents to generate and modify real frontend source code while users inspect, compare, and interact with the result on an infinite canvas.

Analyzes a GitHub repository and user to filter meaningful commits and generate a Cursor Canvas (.canvas.tsx) inclusion tree.

Connects Canvas LMS to AI assistants, enabling users to list courses and retrieve assignment details through natural language. It features secure multi-institution support with encrypted token storage and a simplified setup process for students.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables MCP clients to turn Make blueprints and Zapier exports into n8n workflow files, with a per-step report of what converted, what to review, and what must be finished by hand. Also lists zaps, explains how individual steps are handled, checks workflow files for broken links or placeholders, and can upload the result to an n8n instance as an inactive workflow.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

A Model Context Protocol server that converts Markdown content to HTML format.

An MCP server for Claude Code that enables the creation and manipulation of professional-grade SVG graphics using features like layer management, complex path drawing, and animations. It includes AI-assisted design capabilities for color suggestions and layout optimization, supporting exports to SVG and PNG formats.

Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.