Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
제작자가 쓴 설명(영어 원문)
Reads a summary out loud when an AI coding task finishes. Offline or neural voices.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
VOICE_ENGINE, VOICE_LANGUAGE, VOICE_GENDER, VOICE_RATE, VOICE_VOLUME, VOICE_MUTE, VOICE_MODE필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"voice-summary": {
"command": "uvx",
"args": [
"mcp-voice-summary"
],
"env": {
"VOICE_ENGINE": "your-value",
"VOICE_LANGUAGE": "your-value",
"VOICE_GENDER": "your-value",
"VOICE_RATE": "your-value",
"VOICE_VOLUME": "your-value",
"VOICE_MUTE": "your-value",
"VOICE_MODE": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add voice-summary --env VOICE_ENGINE=your-value --env VOICE_LANGUAGE=your-value --env VOICE_GENDER=your-value --env VOICE_RATE=your-value --env VOICE_VOLUME=your-value --env VOICE_MUTE=your-value --env VOICE_MODE=your-value -- uvx mcp-voice-summary실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"voice-summary": {
"command": "uvx",
"args": [
"mcp-voice-summary"
],
"env": {
"VOICE_ENGINE": "your-value",
"VOICE_LANGUAGE": "your-value",
"VOICE_GENDER": "your-value",
"VOICE_RATE": "your-value",
"VOICE_VOLUME": "your-value",
"VOICE_MUTE": "your-value",
"VOICE_MODE": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"voice-summary": {
"type": "stdio",
"command": "uvx",
"args": [
"mcp-voice-summary"
],
"env": {
"VOICE_ENGINE": "your-value",
"VOICE_LANGUAGE": "your-value",
"VOICE_GENDER": "your-value",
"VOICE_RATE": "your-value",
"VOICE_VOLUME": "your-value",
"VOICE_MUTE": "your-value",
"VOICE_MODE": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
VOICE_ENGINE envVOICE_LANGUAGE envVOICE_GENDER envVOICE_RATE envVOICE_VOLUME envVOICE_MUTE envVOICE_MODE env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 eduplopez 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.1)은 34일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
A local MCP server that reads out loud a summary of the actions an AI assistant just performed on your code. Built as an accessibility layer: you hear what the agent did without having to read the full response.
Speaks in the user's language automatically, with female and male voices, and works fully offline if you want it to.
pip install mcp-voice-summary
Then point your MCP client at the installed command. For Claude Desktop, Cursor or Cline, in claude_desktop_config.json:
{
"mcpServers": { "voice-summary": { "command": "mcp-voice-summary", "env": { "VOICE_ENGINE": "edge", "VOICE_LANGUAGE": "es", "VOICE_GENDER": "male" } } } }
No env block is needed at all: the server picks the voice from your system language. The values above only pin it.
With uvx, without installing anything:
{
"mcpServers": { "voice-summary": { "command": "uvx", "args": ["mcp-voice-summary"], "env": { "VOICE_ENGINE": "edge" } } } }
This server is also listed in the MCP Registry under io.github.eduplopez/mcp-voice-summary. The registry metadata lives in server.json in this repo.
It is also listed on mcprush, with install commands for several clients and its live security grade:
Then tell your assistant to use it, for example: *"After you finish a task, read a short summary out loud."*
| Platform | Recommended engine | Voice source | Extra install |
|---|---|---|---|
| Windows | edge for quality, sapi5 for offline | System voices, or neural | pip install -e ".[sapi5]" for offline |
| macOS | edge for quality, sapi5 for offline | System voices, or neural | pip install pyttsx3 for offline |
| Linux | edge | Neural voices | pip install ffmpeg for playback |
| Linux offline | sapi5 | espeak-ng | sudo apt install espeak-ng libespeak-ng1 |
The edge engine needs an internet connection on every utterance, because the audio is generated by Microsoft's servers. The sapi5 engine is fully offline.
On Linux the audio player is detected automatically; install ffmpeg (which provides ffplay) or mpg123 if nothing is found.
Windows ships better voices than the three exposed by default, but hides them under a registry key SAPI5 does not read. Run this once as administrator:
powershell -Command "Start-Process powershell -Verb RunAs -ArgumentList '-ExecutionPolicy Bypass -File .\register_voices_onecore.ps1'"
Afterwards Microsoft Laura and Microsoft Pablo become available to sapi5.
Exposes an MCP tool, speak_summary, which the assistant calls after modifying code, creating files or running commands.
The summary length is decided by the assistant based on how much work it did: a short sentence for a small change, or a fuller summary when the task was large or had several steps. See Controlling the summary length.
Playback is asynchronous: the tool queues the text and returns immediately, so speaking never blocks the assistant.
Only the sapi5 engine needs a system dependency (the native synthesizer). The edge engine needs nothing beyond Python.
mcp-voice-summary
The server speaks over stdio, so you will see nothing in the console. That is correct: anything printed to stdout would break the protocol. Ctrl+C to stop.
For the offline engine, install its extra first:
pip install -e ".[sapi5]"
Everything is controlled through environment variables.
| Variable | Values | Default | Description |
|---|---|---|---|
VOICE_ENGINE | edge or sapi5 | sapi5 | Synthesis engine |
VOICE_NAME | voice id or name | auto | Exact voice, overrides everything |
VOICE_LANGUAGE | es, en, pt-BR, auto | system language | Voice language |
VOICE_GENDER | female, male | language default | Voice gender |
VOICE_RATE | 100, 110, -15% | 100 | Speed |
VOICE_VOLUME | 100 | 100 | Volume |
VOICE_PLAYER | path or name | auto-detected | Forced MP3 player |
MAX_SUMMARY_WORDS | integer | 400 | Safety cap on words per summary |
MAX_QUEUE_SIZE | integer | 20 | Maximum summaries waiting to be spoken |
PLAYBACK_TIMEOUT | seconds | 30 | Gives up on playback that never returns |
VOICE_MUTE | 1, true, yes | unset | Silent mode: still queues, plays nothing |
VOICE_REDACT | 0, false, no | on | Set to 0 to stop stripping credentials |
VOICE_RATE_LIMIT | notifications per minute | 30 | Stops a client flooding the queue |
MAX_SUMMARY_AGE | seconds | 120 | Queued summaries older than this are dropped |
VOICE_MODE | full, short | full | short speaks a fixed generic message |
VOICE_RATE and VOICE_VOLUME accept both an absolute notation (the SAPI5 scale, where 100 is normal) and a relative one (+10%, -15%). The server translates automatically into the format each engine requires.
After changing the configuration, restart the MCP client.
Nothing needs configuring for this to work in your language. The server picks the voice on its own. The precedence is:
VOICE_NAME, if set: it always wins as a manual override.set_language, if the assistant called it during the session.VOICE_LANGUAGE, if set in the configuration.Permanently, in the configuration:
"environment": { "VOICE_LANGUAGE": "fr", "VOICE_GENDER": "male" }
Or at runtime, without editing anything. The user can ask in natural language and the assistant calls the tool:
set_language("en") -> Language English (en), gender default
set_language("pt-BR", "male") -> Language Portuguese (pt), gender male set_language("", "f") -> keep the language, switch to a female voice set_language("system") -> back to the OS language set_language("", "any") -> back to the language default gender
A runtime change applies to the following utterances and lasts until the server restarts or the tool is called again with a different value.
Gender only works with the `edge` engine. SAPI5 does not expose the gender
of its voices, so with
sapi5the tool says so instead of pretending. Picking
a gender requires neural voices.
VOICE_LANGUAGE=auto makes the server infer the language from each summary's text.
Use this with caution. Language detection is not reliable on short text, and short summaries are the main use case of this project. Measured with real summaries:
| Text | Actual language | Detected |
|---|---|---|
"Done." | Spanish | Czech (with 100 % confidence) |
"Listo" | Spanish | German |
"Test 123" | anything | French |
"I updated the login endpoint and fixed the dependencies" | English | English |
Detectors return high confidence even when they are wrong, so the errors cannot be filtered out by probability. In short: detection works on long sentences and fails on short ones. For a fixed language, VOICE_LANGUAGE is always more reliable.
If langdetect is not installed, auto logs a warning and falls back to English. The other modes work without that dependency.
The edge engine exposes 142 locales across 322 voices. These 34 languages have both a female and a male voice assigned:
| Language | Female | Male | Language | Female | Male |
|---|---|---|---|---|---|
es | Ximena | Ãlvaro | da | Christel | Jeppe |
en | Ava | Andrew | fi | Noora | Harri |
fr | Vivienne | Rémy | nl | Colette | Maarten |
de | Seraphina | Florian | pl | Zofia | Marek |
it | Elsa | Giuseppe | ru | Svetlana | Dmitry |
pt | Thalita | Antonio | uk | Polina | Ostap |
ca | Joana | Enric | cs | Vlasta | AntonÃn |
gl | Sabela | Roi | sk | Viktoria | Lukáš |
hu | Noémi | Tamás | ro | Alina | Emil |
bg | Kalina | Borislav | el | Athina | Nestoras |
sv | Sofie | Mattias | tr | Emel | Ahmet |
nb | Pernille | Finn | ar | Salma | Shakir |
ja | Nanami | Keita | he | Hila | Avri |
ko | Sun-Hi | Hyunsu | hi | Swara | Madhur |
zh | Xiaoxiao | Yunxian | th | Premwadee | Niwat |
vi | HoaiMy | NamMinh | id | Gadis | Ardi |
ms | Yasmin | Osman |
(Short names; the exact identifiers carry the Neural suffix and can be seen with list_voices or python -m edge_tts --list-voices.)
Of the 142 locales, only 2 have a single gender: the Chinese dialects zh-CN-liaoning and zh-CN-shaanxi. If you ask for a gender that does not exist in the chosen locale, the server logs a warning and uses the available voice instead of going silent.
Languages without curated voices still work: the server searches the 322 voices for the first one matching the requested language and gender. For example, sw (Swahili) resolves to sw-KE-RafikiNeural.
If you request a specific regional variant it is respected, by gender too:
| You ask | Female | Male |
|---|---|---|
en-GB | en-GB-LibbyNeural | en-GB-RyanNeural |
pt-PT | pt-PT-RaquelNeural | pt-PT-DuarteNeural |
es-MX | es-MX-DaliaNeural | es-MX-JorgeNeural |
zh-TW | zh-TW-HsiaoChenNeural | zh-TW-YunJheNeural |
fr-CA | fr-CA-SylvieNeural | fr-CA-ThierryNeural |
The sapi5 engine can only use voices installed on the system, so its language coverage is whatever your operating system provides, and it cannot pick gender. Windows ships with Spanish and English; other languages require adding voices.
Full catalog of all 322 voices:
python -m edge_tts --list-voices
The 45 Spanish voices include:
| Voice | Region |
|---|---|
es-ES-AlvaroNeural | Spain, male |
es-ES-XimenaNeural | Spain, female |
es-ES-ElviraNeural | Spain, female |
es-MX-DaliaNeural | Mexico, female |
es-MX-JorgeNeural | Mexico, male |
es-US-PalomaNeural | United States, female |
Out of the box only three very basic voices are visible. Windows already ships better ones, such as Microsoft Laura and Microsoft Pablo, but registers them under the registry key Speech_OneCore, which SAPI5 does not read.
register_voices_onecore.ps1 copies those keys into the branch SAPI5 does read. Run it once from a PowerShell prompt as administrator:
powershell -Command "Start-Process powershell -Verb RunAs -ArgumentList '-ExecutionPolicy Bypass -File .\register_voices_onecore.ps1'"
It is a read-only copy: no e
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요