Create flashcards and study anything with Rember, the anki flashcards tool using spaced repetition to help you remember
by rember·Updated Apr 13, 2026·Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Local RAG
Local RAG enables semantic document search using retrieval augmented generation (RAG) without external API calls.
Clerk
Securely manage Clerk authentication, users, sessions, orgs, and authorization for seamless identity and access control.
HuggingFace Spaces Connector
Seamlessly connect Hugging Face Spaces with your AI assistants for instant access to powerful AI models—no manual setup
TypeScript Refactoring
TypeScript Refactoring offers advanced TypeScript/JavaScript code analysis and intelligent refactoring for seamless and
Sequential Thinking Multi-Agent System
Orchestrate complex problem-solving with our multi agent system—specialized agents offer deep, structured, and parallel
Rember is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Rember reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We evaluated Rember against two servers with overlapping tools; this profile had the clearer scope statement.
I recommend Rember for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We wired Rember into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
I recommend Rember for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Useful MCP listing: Rember is the kind of server we cite when onboarding engineers to host + tool permissions.
Rember is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Rember is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Rember benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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Claude Desktop configuration
{
"mcpServers": {
"rember": {
"command": "npx",
"args": [
"-y",
"@getrember/mcp"
],
"env": {
"REMBER_API_KEY": "YOUR_REMBER_API_KEY"
}
}
}
}Creates flashcards from conversations or documents and schedules them for spaced repetition review in Rember. Lets you turn any learning material into study cards without leaving Claude.
Rember is an official MCP server published by rember that provides AI assistants with tools and capabilities via the Model Context Protocol. Create flashcards and study anything with Rember, the anki flashcards tool using spaced repetition to help you remember It is categorized under ai ml.
You can install Rember in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
Allow Claude to create flashcards for you with the official Model Context Protocol (MCP) for Rember. Rember helps you study and remember anything you care about by scheduling spaced repetition reviews.
Features and examples:
To run the Rember MCP server using npx, use the following command:
npx -y @getrember/mcp --api-key=YOUR_REMBER_API_KEY
Make sure to replace YOUR_REMBER_API_KEY with your actual Rember api key, which you can find in your Settings page. The API key should follow the format rember_ followed by 32 random characters.
Add the following to your claude_desktop_config.json. See here for more details.
{
"mcpServers": {
"rember": {
"command": "npx",
"args": ["-y", "@getrember/mcp", "--api-key=YOUR_REMBER_API_KEY"]
}
}
}
create_flashcards: Create flashcards with AI. This tool takes a list of notes from Claude, it calls the Rember API to generate a few flashcards for each note. After learning something new in your chat with Claude, you can ask "help me remember this" or "create a few flashcards" or "add to Rember".Here's a collection of lessons we learned while developing the Rember MCP server:
Set up logging to stderr as early as possible, it's essential for debugging
Create a simple MCP tool first and verify Claude can call it properly
Invest time in iterating on the tool description:
Use the tool call response strategically, it's not shown directly to users but interpreted by Claude:
Implement retries for transient errors with suitable timeouts
We collected enough edge cases that testing manually on Claude Desktop (our main target MCP client) became cumbersome. We created a suite of unit tests by simulating Claude Desktop behavior by calling the Claude API with the system prompt from claude.ai. In the current iteration, each test simulates a chat with Claude Desktop for manual inspection and includes a few simple assertions
What's missing:
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.