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

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.

Transforms AI assistants into research-grade cognitive workspaces with systematic reasoning, evidence-based analysis, persistent memory management, and intelligent knowledge discovery.

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.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

Create, validate, read, edit, export, and search JSON Canvas files with an interactive inline viewer, stored privately per user.

MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.

Enables local-first knowledge management for Codex, providing tools for guided discussions, contextual recall, review, and daily topics.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

Metis gives AI agents expert know-how that named reviewers have approved, and only where its recorded conditions match the situation. High-risk situations go to a person. When an agent sees practice depart from procedure, it can send the expert one short question. Every retrieval is recorded on a hash-linked evidence chain.

Provides tools for managing student knowledge graphs, enabling structured representation of courses, assignments, exams, concepts, and study resources.

Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

Rabbithole provides an infinite canvas for learning by allowing users to open documents, select text, ask questions, and receive answers that open as child documents, all running locally via an MCP server.

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.

Enables coding agents to fetch concise business definitions of domain terms from a shared SQLite glossary and record gaps for terms that still need documentation.

Enables AI agents to read, write, search, and manage .klypix canvas files for persistent spatial memory across sessions.

The most feature-complete MCP server for Obsidian vaults. 23 tools and 3 resources for search, read, write, tags, link analysis, graph traversal, and canvas support.

Enables MCP clients to discover and fetch skills, agents, commands, and hooks from the Gen-e2 Lab Registry, and check local inventory compliance against the registry.

Enables AI assistants to fetch YouTube transcripts with timestamps, search within a video, and keep a local searchable memory of every transcript fetched.

A codebase ontology and a cited wiki, both kept as Markdown in one folder on your disk. Typed graph answers — what a change affects, how two concepts connect, which wiki lines lack a citation — and every write lands as a Git diff a person reviews.

Enables agents to build and manage family trees, derive how people are related, and export diagrams or GEDCOM/HTML files through structured tools.

Enables AI assistants to read and edit a spatial canvas board of notes, tasks and ideas through the running desktop app, creating, updating, linking, grouping and arranging nodes, importing files, focusing the view and undoing changes so edits appear instantly and stay reversible.

Gives Claude persistent, local context about how you work, your weekly agenda, and shipped work, with automatic work logging and git integration—all stored privately on your machine.

Imports private ChatGPT conversations into MCP clients like Codex and Claude Code. Provides tools to fetch remote conversation content and serve cached context via local stdio.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

MCP server that gives AI models read/write access to Obsidian vaults with semantic search, link graph analysis, canvas manipulation, and incremental indexing.

Enables comprehensive access to Obsidian vaults through MCP, supporting multi-vault management, knowledge graph analysis, canvas manipulation, dataview queries, template rendering, and periodic notes creation. Provides both local filesystem and remote API connectivity for complete Obsidian integration.

Persistent, local memory for AI coding agents that learns how you work, not just what you said. Supports Claude Code, Codex CLI, Cursor, and any MCP client.

A shared living surface where AI agents leave short thoughts in six currents and weave lineages from each other's words; humans witness the ocean on a canvas. Remote MCP at https://vellum.linxule.com/mcp (6 tools, no auth) plus a REST API and a public echo mailbox so agents can return to see what became of what they said.