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

A local stdio MCP server for visual AI work, offering an Excalidraw infinite canvas, image generation and editing, HTML drafts, presentations, and durable task recovery within a project workspace.

MCP server that renders bar, line, and pie charts from data using QuickChart, returning PNG file paths.

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

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

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Enables agents to create, read, edit, typecheck, compile, and version local React canvas artifacts through MCP, with inline interactive previews in supporting chat clients.

Provides image generation capabilities using Amazon Nova Canvas through Amazon Bedrock, enabling the creation of visuals from text prompts and color palettes—perfect for mockups, diagrams, and UI design concepts.

Lets coding agents fetch real social media and web data from platforms like TikTok, Instagram, YouTube, and more, directly inside editors like Cursor and VS Code.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

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.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

Enables querying of a locally pinned snapshot of the Education-to-Workforce Indicator Framework — 99 indicators and 11.8M observations — to browse questions, describe metrics, resolve places, and fetch or rank data across national, state, county, and district levels.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Enables agents to discover available still-image animation models, obtain credit quotes without charge, submit one explicitly approved generation job, and poll the resulting short clip.

Enables searching government awards through the Sell to State API by proxying JSON-RPC to the live HTTP MCP endpoint, requiring an API key.

Lightweight project management for teams and AI agents.

An MCP server that lets you schedule AI phone calls and manage Leximo assignments directly from Claude Desktop or Claude Code.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

MCP Server to fetch costs and usage data from your Vantage account.

Connects AI assistants to a student's Helium account to import a term from syllabi and read the planner, including assignments, events, notes, classes, resources, and grades. It makes no model calls and uses the student's own OAuth token.

Enables AI systems to fetch machine learning inferences and prediction market data from the Allora Network through the Model Context Protocol.

Enables AI agents to fetch real-time quotes, token information, and trade transaction data from Monorail's aggregation of 11 exchanges and 7000+ tokens.

Provides Figma design context to AI agents, enabling code generation, design system integration, and canvas manipulation through MCP.

Enables MCP clients to inspect Google Play releases, reviews, Android vitals, and scoped bulk reports, and to prepare explicitly authorized changes using locally supplied service-account credentials. Reads are default, while optional writes and sensitive reads require explicit configuration and single-use execution.

Enables AI clients to transcribe YouTube links and uploaded audio or video files, then retrieve the resulting transcripts as text, SRT, VTT, or JSON with timestamps and optional speaker labels. Also supports paging through long transcripts, checking upload progress, listing or deleting jobs, and viewing remaining account minutes.

Enables agents to enrich domains into public business contact data, including MX/disposable-validated role emails, phones, social profiles, company names, and addresses, while respecting robots.txt; also normalizes URLs and emails into unique domains locally.

Live open jobs from companies' own Greenhouse, Lever and Ashby boards via their official public APIs, with publish-verified dates, age, long-open and repost signals, filters and change tracking.

Enables agents to fuzzy-screen person and company names against the OFAC SDN/Consolidated, EU, UK and UN sanctions lists downloaded fresh from official sources, returning potential-match statuses, 0–100 scores and listing details via a billed screening tool, plus a free local tool that lists covered sources, score scale and disclaimer.