What can AnkiConnect do?

anki deck and card crud operations via mcp protocol, anki card review and scheduling state management, anki note field templating and card generation, anki collection synchronization and backup management, anki media file management and attachment handling, anki deck and card search with filtering, anki deck organization and hierarchy management, anki tag management and bulk tagging operations

AnkiConnect

MCP ServerFree

** - AnkiConnect MCP server for interacting with Anki via AnkiConnect.

Open Source

/ 100

8 capabilities

Capabilities8 decomposed

anki deck and card crud operations via mcp protocol

Medium confidence

Exposes AnkiConnect's REST API endpoints as MCP tools, enabling programmatic creation, reading, updating, and deletion of Anki decks, cards, and notes. Works by translating MCP tool calls into HTTP requests to the AnkiConnect server (typically running on localhost:8765), then marshaling JSON responses back to the MCP client. Supports batch operations for bulk card creation and modification.

Solves for

I want to programmatically add flashcards to my Anki deck from an external data sourceI need to bulk-update card fields or tags across multiple notesI want to create a new deck and populate it with cards via an AI agentI need to retrieve card data for analysis or export

Best for

AI agents and LLM-based workflows that need persistent spaced-repetition learning

Developers building study automation tools that integrate with Anki

Non-technical users using Claude or other LLM clients with MCP support who want to manage Anki decks conversationally

Requires

Anki desktop application installed and running

AnkiConnect add-on (https://github.com/FooSoft/anki-connect) installed in Anki

AnkiConnect server listening on localhost:8765 (or configured remote host)

Limitations

Requires AnkiConnect server to be running separately on the host machine — no embedded Anki runtime

Network latency between MCP server and AnkiConnect adds ~50-200ms per operation

Batch operations are sequential, not truly parallel — large bulk imports may be slow

What makes it unique

Bridges the gap between LLM agents and Anki by wrapping AnkiConnect's REST API as MCP tools, allowing Claude and other MCP-capable clients to manage Anki decks natively without custom integrations. Uses MCP's tool schema to expose AnkiConnect operations with proper type safety and parameter validation.

vs alternatives

Unlike direct AnkiConnect API calls or custom Python scripts, this MCP server integrates seamlessly with Claude and other LLM clients, enabling conversational deck management without leaving the chat interface.

anki card review and scheduling state management

Medium confidence

Provides MCP tools to query and manipulate card review states, including ease factors, interval spacing, and due dates. Translates MCP calls into AnkiConnect API requests that interact with Anki's SQLite database through the AnkiConnect bridge. Enables agents to inspect review history, reschedule cards, and reset learning progress programmatically.

Solves for

I want to check which cards are due for review todayI need to reschedule a card to a different due dateI want to reset a card's learning progress and start overI need to query cards by review status (new, learning, review, suspended)

Best for

Study optimization agents that adjust review schedules based on performance

Developers building custom spaced-repetition algorithms on top of Anki

Researchers analyzing learning patterns and card difficulty metrics

Requires

Anki desktop application with AnkiConnect add-on running

AnkiConnect server accessible at configured endpoint

MCP client with tool-calling capability

Limitations

Read-only access to some scheduling metadata — cannot directly modify Anki's internal SM-2 algorithm parameters

Scheduling changes are applied immediately without validation against Anki's internal consistency rules

No transaction support — bulk scheduling updates are not atomic

What makes it unique

Exposes Anki's scheduling state as queryable MCP tools, allowing agents to make data-driven decisions about review timing. Unlike direct database access, this approach maintains AnkiConnect's abstraction layer, ensuring compatibility across Anki versions and preventing database corruption.

vs alternatives

Provides scheduling introspection without requiring direct SQLite access or reverse-engineering Anki's database schema, making it safer and more maintainable than raw database manipulation.

anki note field templating and card generation

Medium confidence

Enables MCP clients to define note types with custom fields and card templates, then generate cards from structured data. Works by translating template definitions into AnkiConnect API calls that create or update note types in the Anki collection. Supports field mapping, conditional rendering, and bulk card generation from tabular data sources.

Solves for

I want to create a custom note type with specific fields (e.g., word, definition, example, pronunciation)I need to generate 100 flashcards from a CSV file with consistent formattingI want to define a card template that renders different content on front vs. backI need to map data from an external API (e.g., dictionary, translation service) into Anki cards

Best for

Language learners building vocabulary decks from structured data

Educators creating standardized note types for student use

AI agents that generate study materials from documents or web content

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Template syntax is limited to AnkiConnect's subset of Anki's templating language — advanced HTML/CSS customization requires manual Anki editing

Field validation is minimal — invalid field names or circular template references may cause silent failures

No preview of rendered cards before bulk import

What makes it unique

Abstracts Anki's note type and card template system as MCP tools, allowing non-Anki-expert users and agents to define custom card formats programmatically. Handles the complexity of AnkiConnect's template API, which requires understanding Anki's internal field syntax and rendering rules.

vs alternatives

Simpler than manually editing Anki's note type UI or writing raw AnkiConnect JSON; enables template-driven card generation workflows that integrate with LLM agents.

anki collection synchronization and backup management

Medium confidence

Provides MCP tools to trigger Anki collection syncs with AnkiWeb, export decks to APKG files, and manage backup snapshots. Translates MCP calls into AnkiConnect API requests that coordinate with Anki's sync engine and file export routines. Enables agents to ensure data consistency across devices and create recovery points.

Solves for

I want to sync my Anki collection to AnkiWeb before making bulk changesI need to export a deck as an APKG file for sharing or backupI want to create a backup snapshot before running an automated deck updateI need to check the sync status and resolve conflicts

Best for

Automated study workflows that need to ensure data consistency before and after bulk operations

Backup and disaster-recovery automation

Multi-device study setups that rely on AnkiWeb synchronization

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

AnkiWeb account for sync operations (optional, but required for cloud sync)

Limitations

Sync conflicts are not automatically resolved — requires manual intervention in Anki UI

Export operations are blocking and may take several seconds for large decks

No incremental backup support — each export is a full deck snapshot

What makes it unique

Wraps Anki's sync and export operations as MCP tools, enabling agents to manage collection consistency and create recovery points as part of automated workflows. Integrates with AnkiWeb's sync protocol through AnkiConnect's abstraction, avoiding direct authentication or protocol handling.

vs alternatives

Safer than direct file manipulation or database exports; leverages Anki's native sync and export logic to ensure data integrity and compatibility with AnkiWeb.

anki media file management and attachment handling

Medium confidence

Provides MCP tools to add, retrieve, and manage media files (images, audio, video) attached to Anki cards. Works by translating MCP calls into AnkiConnect API requests that handle file uploads, storage in Anki's media folder, and reference management in card fields. Supports batch media imports and URL-based media fetching.

Solves for

I want to add pronunciation audio to vocabulary cardsI need to attach images to flashcards (e.g., anatomy diagrams, flags)I want to bulk-import media files from a folder and link them to cardsI need to retrieve media URLs for cards to display in external applications

Best for

Language learning decks with audio and image content

Visual learners building image-heavy study materials

Educators creating multimedia study resources

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

Media files accessible locally or via URL

Limitations

Media file size limits depend on AnkiConnect and Anki's configuration — typically 100MB+ per file

No built-in image optimization or compression — large images may slow down Anki

Media references are stored as file names in card fields — moving or renaming files breaks references

What makes it unique

Abstracts Anki's media folder management and file reference system as MCP tools, allowing agents to handle media attachments without understanding Anki's internal file naming and storage conventions. Supports multiple input formats (local files, URLs, base64) for flexibility.

vs alternatives

Simpler than manually managing Anki's media folder or writing custom file handling code; integrates media operations into the same MCP workflow as card creation and scheduling.

anki deck and card search with filtering

Medium confidence

Provides MCP tools to query Anki's card database using AnkiConnect's search syntax, enabling agents to find cards by field content, tags, review status, and custom criteria. Translates MCP search parameters into AnkiConnect API calls that execute against the Anki collection's SQLite database. Returns structured card data for further processing or analysis.

Solves for

I want to find all cards with a specific tag or tag combinationI need to search for cards containing certain text in a fieldI want to find cards due for review in the next 7 daysI need to identify cards with low ease factors or high failure rates

Best for

Study analytics and reporting workflows

Agents that need to identify cards for targeted review or remediation

Deck maintenance tasks (finding duplicates, orphaned cards, etc.)

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Search syntax is limited to AnkiConnect's query language — complex boolean logic may require multiple queries

Search performance degrades with very large collections (100k+ cards)

No full-text search across all fields — searches are field-specific

What makes it unique

Exposes AnkiConnect's search API as MCP tools with parameter validation and result structuring, allowing agents to query Anki collections without learning AnkiConnect's search syntax. Supports chaining searches for complex filtering workflows.

vs alternatives

More flexible than pre-defined queries; integrates with LLM agents that can construct dynamic search criteria based on user intent or analysis results.

anki deck organization and hierarchy management

Medium confidence

Provides MCP tools to create, rename, move, and delete decks, as well as manage deck hierarchies (parent-child relationships). Works by translating MCP calls into AnkiConnect API requests that manipulate Anki's deck tree structure. Supports bulk deck operations and validation of deck names against Anki's naming conventions.

Solves for

I want to organize my decks into a hierarchical structure (e.g., Languages > Spanish > Vocabulary)I need to rename a deck or move cards between decksI want to create a new deck for a specific study topicI need to delete unused decks and consolidate my collection

Best for

Users managing large, multi-topic Anki collections

Educators organizing decks for multiple courses or student groups

Automated workflows that create temporary decks for specific tasks

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Deck names must follow Anki's conventions (no special characters, max length ~250 chars)

Moving cards between decks is not atomic — large moves may be slow

Deleting a deck also deletes all cards in it — no soft delete or recovery

What makes it unique

Abstracts Anki's deck tree structure as MCP tools, enabling agents to organize collections programmatically without manual UI interaction. Validates deck names and hierarchies against Anki's constraints before applying changes.

vs alternatives

Simpler than manual deck management in Anki's UI; enables automated organization workflows that adapt to changing study needs or data sources.

anki tag management and bulk tagging operations

Medium confidence

Provides MCP tools to add, remove, and rename tags across cards, as well as query cards by tag. Works by translating MCP calls into AnkiConnect API requests that manipulate Anki's tag database and card-tag associations. Supports bulk tagging operations and tag hierarchy management (using :: notation).

Solves for

I want to add a tag to multiple cards at once (e.g., marking cards as 'review-needed')I need to rename a tag across all cards that use itI want to organize tags hierarchically (e.g., 'language::spanish::vocabulary')I need to find all cards with a specific tag for targeted study

Best for

Study workflows that use tags for organization and filtering

Agents that categorize cards based on difficulty, topic, or review status

Bulk tagging operations during deck imports or migrations

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Tag operations are not atomic — bulk tagging large numbers of cards may be slow

Tag hierarchies are simulated using :: notation — no true parent-child relationships

Renaming a tag does not automatically update all references — requires explicit bulk operation

What makes it unique

Exposes Anki's tag system as MCP tools with support for hierarchical tagging (:: notation) and bulk operations, enabling agents to organize and filter cards by semantic categories. Validates tag names and handles tag renaming across the entire collection.

vs alternatives

More powerful than manual tagging in Anki's UI; enables dynamic tagging workflows that adapt to card content or review performance.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with AnkiConnect, ranked by overlap. Discovered automatically through the match graph.

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Trello

** - Trello integration for working with boards, lists in boards and cards in lists.

card-creation-and-mutation

1 shared capability

Product31

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Unlock personalized and AI-driven flashcard creation for efficient and effective...

flashcard set creation and organization

1 shared capability

Best For

✓AI agents and LLM-based workflows that need persistent spaced-repetition learning
✓Developers building study automation tools that integrate with Anki
✓Non-technical users using Claude or other LLM clients with MCP support who want to manage Anki decks conversationally
✓Study optimization agents that adjust review schedules based on performance
✓Developers building custom spaced-repetition algorithms on top of Anki
✓Researchers analyzing learning patterns and card difficulty metrics
✓Language learners building vocabulary decks from structured data
✓Educators creating standardized note types for student use

Known Limitations

⚠Requires AnkiConnect server to be running separately on the host machine — no embedded Anki runtime
⚠Network latency between MCP server and AnkiConnect adds ~50-200ms per operation
⚠Batch operations are sequential, not truly parallel — large bulk imports may be slow
⚠No built-in conflict resolution for concurrent edits from multiple MCP clients
⚠Read-only access to some scheduling metadata — cannot directly modify Anki's internal SM-2 algorithm parameters
⚠Scheduling changes are applied immediately without validation against Anki's internal consistency rules

Requirements

Anki desktop application installed and runningAnkiConnect add-on (https://github.com/FooSoft/anki-connect) installed in AnkiAnkiConnect server listening on localhost:8765 (or configured remote host)MCP client that supports tool calling (Claude, or other LLM with MCP support)Anki desktop application with AnkiConnect add-on runningAnkiConnect server accessible at configured endpointMCP client with tool-calling capabilityAnki desktop application with AnkiConnect add-on

Input / Output

Accepts: JSON-structured note objects with fields (front, back, tags, deck name), Deck names as strings, Card IDs as integers, Query strings for card filtering, Unix timestamps for due dates, Ease factor values (1.3–2.5 range), Interval values in days, JSON note type definitions with field names and types, Card template strings with field placeholders, Tabular data (JSON arrays of objects) for bulk card generation, Deck names for export, AnkiWeb credentials (if syncing), File paths for backup storage, File paths to local media files, URLs for remote media (images, audio), Base64-encoded media data, Card IDs for media attachment, Search query strings (AnkiConnect syntax), Tag names or tag combinations, Field names and search terms, Review status filters (new, learning, review, suspended), Deck names (strings), Parent deck names for hierarchy, Card IDs for moving between decks, Tag names (strings), Card IDs for tagging operations, Old and new tag names for renaming

Produces: JSON responses with card IDs, note IDs, or operation status, Structured card data (fields, tags, review history metadata), Boolean success/failure indicators, Card review metadata (due date, interval, ease, review count), Lists of card IDs filtered by review status, Boolean confirmation of scheduling updates, Note type IDs and confirmation of creation, Lists of generated card IDs, Error messages for invalid templates or field mappings, APKG file paths, Sync status indicators (success, conflict, error), Backup metadata (timestamp, deck count, card count), Media file names as stored in Anki, Media URLs for retrieval, Confirmation of successful attachment, Lists of card IDs matching the search criteria, Card count, Structured card data (fields, tags, review metadata), Deck IDs and confirmation of creation/deletion, Updated deck hierarchy structure, Lists of cards moved between decks, Confirmation of tagging operations, Lists of cards with specific tags, Tag counts and statistics

UnfragileRank

Adoption15%(25% weight)

Quality17%(25% weight)

Ecosystem30%(15% weight)

Match Graph25%(30% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

8 capabilities

Visit AnkiConnect→

About

** - AnkiConnect MCP server for interacting with Anki via AnkiConnect.

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Capabilities8 decomposed

anki deck and card crud operations via mcp protocol

Medium confidence

Solves for

Best for

AI agents and LLM-based workflows that need persistent spaced-repetition learning

Developers building study automation tools that integrate with Anki

Non-technical users using Claude or other LLM clients with MCP support who want to manage Anki decks conversationally

Requires

Anki desktop application installed and running

AnkiConnect add-on (https://github.com/FooSoft/anki-connect) installed in Anki

AnkiConnect server listening on localhost:8765 (or configured remote host)

Limitations

Requires AnkiConnect server to be running separately on the host machine — no embedded Anki runtime

Network latency between MCP server and AnkiConnect adds ~50-200ms per operation

Batch operations are sequential, not truly parallel — large bulk imports may be slow

What makes it unique

vs alternatives

anki card review and scheduling state management

Medium confidence

Solves for

Best for

Study optimization agents that adjust review schedules based on performance

Developers building custom spaced-repetition algorithms on top of Anki

Researchers analyzing learning patterns and card difficulty metrics

Requires

Anki desktop application with AnkiConnect add-on running

AnkiConnect server accessible at configured endpoint

MCP client with tool-calling capability

Limitations

Read-only access to some scheduling metadata — cannot directly modify Anki's internal SM-2 algorithm parameters

Scheduling changes are applied immediately without validation against Anki's internal consistency rules

No transaction support — bulk scheduling updates are not atomic

What makes it unique

vs alternatives

Provides scheduling introspection without requiring direct SQLite access or reverse-engineering Anki's database schema, making it safer and more maintainable than raw database manipulation.

anki note field templating and card generation

Medium confidence

Solves for

Best for

Language learners building vocabulary decks from structured data

Educators creating standardized note types for student use

AI agents that generate study materials from documents or web content

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Template syntax is limited to AnkiConnect's subset of Anki's templating language — advanced HTML/CSS customization requires manual Anki editing

Field validation is minimal — invalid field names or circular template references may cause silent failures

No preview of rendered cards before bulk import

What makes it unique

vs alternatives

Simpler than manually editing Anki's note type UI or writing raw AnkiConnect JSON; enables template-driven card generation workflows that integrate with LLM agents.

anki collection synchronization and backup management

Medium confidence

Solves for

Best for

Automated study workflows that need to ensure data consistency before and after bulk operations

Backup and disaster-recovery automation

Multi-device study setups that rely on AnkiWeb synchronization

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

AnkiWeb account for sync operations (optional, but required for cloud sync)

Limitations

Sync conflicts are not automatically resolved — requires manual intervention in Anki UI

Export operations are blocking and may take several seconds for large decks

No incremental backup support — each export is a full deck snapshot

What makes it unique

vs alternatives

Safer than direct file manipulation or database exports; leverages Anki's native sync and export logic to ensure data integrity and compatibility with AnkiWeb.

anki media file management and attachment handling

Medium confidence

Solves for

Best for

Language learning decks with audio and image content

Visual learners building image-heavy study materials

Educators creating multimedia study resources

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

Media files accessible locally or via URL

Limitations

Media file size limits depend on AnkiConnect and Anki's configuration — typically 100MB+ per file

No built-in image optimization or compression — large images may slow down Anki

Media references are stored as file names in card fields — moving or renaming files breaks references

What makes it unique

vs alternatives

Simpler than manually managing Anki's media folder or writing custom file handling code; integrates media operations into the same MCP workflow as card creation and scheduling.

anki deck and card search with filtering

Medium confidence

Solves for

Best for

Study analytics and reporting workflows

Agents that need to identify cards for targeted review or remediation

Deck maintenance tasks (finding duplicates, orphaned cards, etc.)

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Search syntax is limited to AnkiConnect's query language — complex boolean logic may require multiple queries

Search performance degrades with very large collections (100k+ cards)

No full-text search across all fields — searches are field-specific

What makes it unique

vs alternatives

More flexible than pre-defined queries; integrates with LLM agents that can construct dynamic search criteria based on user intent or analysis results.

anki deck organization and hierarchy management

Medium confidence

Solves for

Best for

Users managing large, multi-topic Anki collections

Educators organizing decks for multiple courses or student groups

Automated workflows that create temporary decks for specific tasks

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Deck names must follow Anki's conventions (no special characters, max length ~250 chars)

Moving cards between decks is not atomic — large moves may be slow

Deleting a deck also deletes all cards in it — no soft delete or recovery

What makes it unique

vs alternatives

Simpler than manual deck management in Anki's UI; enables automated organization workflows that adapt to changing study needs or data sources.

anki tag management and bulk tagging operations

Medium confidence

Solves for

Best for

Study workflows that use tags for organization and filtering

Agents that categorize cards based on difficulty, topic, or review status

Bulk tagging operations during deck imports or migrations

Requires

Anki desktop application with AnkiConnect add-on

AnkiConnect server running

MCP client with tool-calling support

Limitations

Tag operations are not atomic — bulk tagging large numbers of cards may be slow

Tag hierarchies are simulated using :: notation — no true parent-child relationships

Renaming a tag does not automatically update all references — requires explicit bulk operation

What makes it unique

vs alternatives

More powerful than manual tagging in Anki's UI; enables dynamic tagging workflows that adapt to card content or review performance.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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AnkiConnect

Capabilities8 decomposed

anki deck and card crud operations via mcp protocol

anki card review and scheduling state management

anki note field templating and card generation

anki collection synchronization and backup management

anki media file management and attachment handling

anki deck and card search with filtering

anki deck organization and hierarchy management

anki tag management and bulk tagging operations

Related Artifactssharing capabilities

AnkiDecks AI

AnkiDecks AI

Rember

KardsAI

Trello

OmniSets

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to AnkiConnect

Are you the builder of AnkiConnect?

Get the weekly brief

Data Sources

AnkiConnect

Capabilities8 decomposed

anki deck and card crud operations via mcp protocol

anki card review and scheduling state management

anki note field templating and card generation

anki collection synchronization and backup management

anki media file management and attachment handling

anki deck and card search with filtering

anki deck organization and hierarchy management

anki tag management and bulk tagging operations

Related Artifactssharing capabilities

AnkiDecks AI

AnkiDecks AI

Rember

KardsAI

Trello

OmniSets

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to AnkiConnect

Are you the builder of AnkiConnect?

Get the weekly brief

Data Sources