"Anki" matching MCP servers:

A Model Context Protocol server that enables LLMs to interact with Anki flashcard software through AnkiConnect, allowing for creation and management of flashcards, decks, and note types.

Server that enables programmatic interaction with Anki through the Model Context Protocol, allowing users to manage flashcards, decks, and review processes.

A Model Context Protocol server that enables language models to interact with Anki flashcard decks programmatically, with specialized features for Japanese language learning including vocabulary import, sample sentence generation, and spaced repetition review.

Enables AI assistants to control Anki Vector robots locally via natural language, providing tools for speech, motion, perception, and interaction without cloud dependency.

Enables analysis of claims, validation of sources, and detection of manipulation using multiple epistemological frameworks to ensure credible and ethical information.

Enables autonomous web browsing and extraction by canonicalizing URLs, detecting anti-crawler traps such as circular paths and infinite pagination, pruning DOM content, mapping forms, converting tables to JSON, and evaluating agent trajectories.

Verified MCP proxy from Agent Trust: every tools/call is checked against your organisation's policy before it reaches the server, with an evidence list; escalations wait for a human approval and every decision lands in a signed ledger.

Enables personal AI agents and users to reinforce habits, triage decisions, and prevent streak-break abandonment by generating adaptive micro-fallbacks and elastic recommendations.

Enables autonomous web agents to canonicalize URLs, detect anti-crawler traps such as circular paths and infinite pagination, prune DOM tokens, auto-map forms, transform tables into JSON, and evaluate action trajectories through MCP.

Enables large language models to interact with ROS robots seamlessly, allowing natural language control, real-time sensor monitoring, and autonomous task execution without modifying existing robot code.

Enables personal agents to track habits and receive adaptive micro-fallbacks that degrade gracefully when a streak is missed, rather than letting the user abandon it. Surfaces prioritized queues and elastic recommendations through MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.

Exposes EnergyPlus simulation control (run, parse metrics, edit schedules) as LLM tools for autonomous building energy optimization.