AnkiConnect▌
by samefarrar
Integrate Anki flashcards with AnkiConnect for natural language, spaced repetition learning in conversations. Easy acces
Integrates Anki flashcard functionality, enabling natural language interactions for spaced repetition learning within conversations.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Students doing daily flashcard reviews
- / Language learners using spaced repetition
- / Anyone wanting conversational flashcard practice
capabilities
- / Check how many cards are due today
- / Retrieve due flashcards for review
- / Submit review answers with difficulty ratings
- / Filter cards by specific decks
- / Control number of cards shown per session
what it does
Connects Claude to Anki flashcards through AnkiConnect, letting you review cards and create flashcards through natural conversation.
about
AnkiConnect is a community-built MCP server published by samefarrar that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Anki flashcards with AnkiConnect for natural language, spaced repetition learning in conversations. Easy acces It is categorized under productivity, developer tools.
how to install
You can install AnkiConnect 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.
license
MIT
AnkiConnect is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
mcp-ankiconnect MCP server
Connect Claude conversations with AnkiConnect via MCP to make spaced repetition as easy as "Let's go through today's flashcards" or "Make flashcards for this"
Components
Tools
The server implements three tools:
-
num_cards_due_today: Get the number of cards due today- Optional
deckargument to filter by specific deck - Returns count of due cards across all decks or specified deck
- Optional
-
get_due_cards: Get cards that are due for review- Optional
limitargument (default: 5) to control number of cards - Optional
deckargument to filter by specific deck - Optional
today_onlyargument (default: true) to show only today's cards - Returns cards in XML format with questions and answers
- Optional
-
submit_reviews: Submit answers for reviewed cards- Takes list of
reviewswithcard_idandrating - Ratings: "wrong", "hard", "good", "easy"
- Returns confirmation of submitted reviews
- Takes list of
Configuration
Prerequisites
- Anki must be running with AnkiConnect plugin installed (plugin id 2055492159)
AnkiConnect can be slow on Macs due to the AppSleep feature, so disable it for Anki. To do so run the following in your terminal.
defaults write net.ankiweb.dtop NSAppSleepDisabled -bool true defaults write net.ichi2.anki NSAppSleepDisabled -bool true defaults write org.qt-project.Qt.QtWebEngineCore NSAppSleepDisabled -bool true
Installation
Quickstart
-
Install the AnkiConnect plugin in Anki:
- Tools > Add-ons > Get Add-ons...
- Enter code:
2055492159 - Restart Anki
-
Configure Claude Desktop:
On MacOS:
~/Library/Application\ Support/Claude/claude_desktop_config.jsonOn Windows:%APPDATA%/Claude/claude_desktop_config.jsonAdd this configuration:
{ "mcpServers": { "mcp-ankiconnect": { "command": "uv", "args": ["run", "--with", "mcp-ankiconnect", "mcp-ankiconnect"] } } } -
Restart Anki and Claude desktop
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector. First, clone the repository and install the dependencies:
git clone https://github.com/samefarrar/mcp-ankiconnect.git
cd mcp-ankiconnect
uv sync
You can launch the MCP Inspector via the mcp CLI:
uv run mcp dev mcp_ankiconnect/server.py
Upon launching, the Inspector will display a URL you can access in your browser to begin debugging.
FAQ
- What is the AnkiConnect MCP server?
- AnkiConnect is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for AnkiConnect?
- This profile displays 51 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
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
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ 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.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★51 reviews- ★★★★★Olivia Menon· Dec 28, 2024
We wired AnkiConnect into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Aisha Liu· Dec 28, 2024
Useful MCP listing: AnkiConnect is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Luis Malhotra· Dec 24, 2024
AnkiConnect is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Pratham Ware· Dec 16, 2024
AnkiConnect is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Dhruvi Jain· Dec 12, 2024
AnkiConnect has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Mei Johnson· Dec 4, 2024
According to our notes, AnkiConnect benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Li Verma· Nov 23, 2024
AnkiConnect has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Li Tandon· Nov 19, 2024
Strong directory entry: AnkiConnect surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Lucas Khanna· Nov 19, 2024
AnkiConnect reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Oshnikdeep· Nov 3, 2024
According to our notes, AnkiConnect benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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