Obsidianki MCP Server
Generates flashcards and integrates with Anki to create or update decks and cards using the obsidianki tool.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Obsidianki MCP Servergenerate 4 cards from notes on machine learning"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Obsidianki MCP Server
MCP server for generating flashcards using obsidianki.
Prerequisites
obsidianki installed and available in PATH, >= 0.7
Related MCP server: Anki MCP Server
Installation
Add to your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"obsidianki-mcp": {
"command": "uvx",
"args": ["obsidianki-mcp"]
}
}
}Usage
The server provides one tool: generate_flashcards
Parameters
notes(optional): List of note patterns to processExamples:
["frontend/*"],["docs/*.md:3"]Supports glob patterns with optional sampling using
:Nsuffix
cards(optional): Number of flashcards to generate (recommend 3-6)query(optional): Query/topic for generating content from chatdeck(optional): Deck name (defaults to your default deck)use_schema(optional): Use existing cards from deck to match format
Available Tools
1 toolgenerate_flashcardsA
Generate flashcards using obsidianki.
Args:
notes: Note patterns to process (e.g., ["frontend/*", "docs/*.md:3"]). Supports glob patterns with optional sampling using :N suffix. You can leave this blank if the user does not specify.
cards: Number of flashcards to generate (number of cards to generate, recommend 3-6 if set)
query: Optional query/topic for generating content from chat. Important for generating new content rather than from existing notes.
deck: Optional deck name (defaults to user's default deck)
use_schema: If true, uses existing cards from the deck to match specific card format (--use-schema flag)
| Name | Required | Description | Default |
|---|---|---|---|
| notes | No | ||
| cards | No | ||
| query | No | ||
| deck | No | ||
| use_schema | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose behavioral traits such as permissions required, side effects (e.g., file creation/modification), safety guarantees, or expected behavior when parameters are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a single line purpose followed by a clear, well-structured parameter list. It is front-loaded and each sentence contributes, though could be slightly tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (context signal), the description is mostly complete. However, it lacks explanation of what happens when both notes and query are empty, and could clarify the output format more, though the output schema may cover that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds significant value by explaining each parameter: notes supports glob with sampling, cards has a recommended range, query is for new content, deck defaults, and use_schema reuses existing cards, all beyond the schema's type/default information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Generate flashcards using obsidianki,' which clearly states the verb (generate) and resource (flashcards). It is specific and easily understood, with no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage hints for individual parameters (e.g., 'You can leave this blank if the user does not specify' for notes, 'recommend 3-6 if set' for cards), but lacks explicit guidance on when to use this tool versus alternatives or overall context for its application.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.1- First observed
generate_flashcards
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of confusion between tools. The tool's purpose is clearly defined.
The single tool uses a clear verb_noun pattern ('generate_flashcards'), which is consistent within the server.
The server has only one tool, which is the bare minimum. For a single-purpose server focused on generating flashcards, this is borderline but not excessive.
The tool only supports generation. There are no tools for viewing, updating, or deleting flashcards, creating significant gaps for any workflow beyond initial generation.
Maintenance
Related MCP Connectors
Search your Obsidian vault to quickly find notes by title or keyword, summarize related content, a…
- FlipnemOAuthcom.flipnem
Build and study spaced-repetition flashcards with your agent.
AI-powered YouTube to flashcards with spaced repetition and Anki export
Spaced-repetition flashcards your AI writes, quizzes you on by voice, and schedules with FSRS.
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