anki-mcp-server

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Add pronunciation audio

anki_generate_audio

Idempotent

Generate text-to-speech audio for Anki notes matching a search query, filling only empty destination fields. Convert field text to [sound:] clips via Google or AwesomeTTS voices.

Instructions

Add text-to-speech audio to notes matching an Anki search (e.g. 'deck:"Spanish" added:1'). Only notes whose dest_field is empty are processed; nothing is overwritten.

source_field: field whose text is spoken. dest_field: field that receives [sound:...] (e.g. "Back" or an "Audio" field). Works out of the box. engine: "google" = built-in, free Google Translate voices, needs internet; the text is sent to Google. "awesometts" = your AwesomeTTS add-on voice (needs AwesomeTTS + the bridge add-on). "auto" (default) = AwesomeTTS if available, else google. lang: language code for google (e.g. "en", "es", "fr", "de", "ja", "zh-CN"); see anki_tts_status. accent: Google domain for regional accents with lang "en": "com" (US), "co.uk", "com.au", "ca", "co.in". preset: AwesomeTTS preset name (or "group:"); default = the voice last used in AwesomeTTS.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>",
      "source_field": "<source_field>",
      "dest_field": "<dest_field>"
    },
    "name": "anki_generate_audio"
  }
}

Input Schema

Name	Required	Default
`lang`	No	en
`limit`	No
`query`	Yes
`accent`	No	com
`engine`	No	auto
`preset`	No
`dry_run`	No
`dest_field`	Yes
`source_field`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Nov 4, 2026

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare non-read-only, non-destructive, idempotent, open-world behavior, and the description adds real context beyond them: nothing is overwritten because only empty dest_fields are filled, and with 'google' the note text is sent to an external service. It does not explain the limit cap, what dry_run does, or failure behavior on partially processed notes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core behavior and its safety guarantee are front-loaded in the first two lines, followed by a compact per-parameter glossary. It is dense but every line carries information; only the trailing blank formatting and the unexplained params keep it from a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a nine-parameter, mutation-capable tool with an output schema (so return values need no explanation), the description covers the risky parts: non-overwrite guarantee, external data transmission, and dependency requirements for the AwesomeTTS path. The omission of limit and dry_run semantics is the notable remaining gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the load, and it does for seven of nine parameters — source_field, dest_field (with example values), engine (all three enum values explained), lang, accent (Google domains tied to lang 'en'), preset, and query via the search example. The remaining two, limit and dry_run, are undocumented in both the schema and the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence names a specific verb and resource ('Add text-to-speech audio to notes') and scopes it to notes matching an Anki search with a concrete query example. It also points to the sibling anki_tts_status for language codes, so an agent can place it among the other anki_* tools without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states the key operating condition — only notes whose dest_field is empty are processed — and gives explicit selection criteria for each engine ('google' needs internet, 'awesometts' needs the add-on plus bridge, 'auto' prefers AwesomeTTS). It lacks an explicit when-not-to-use statement (e.g. for notes already having audio, or when to prefer anki_update_notes), which keeps it below a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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