Gemini Tts Mcp

io.github.runapi-builder由 GitHub 帳號 runapi-builder 發布v0.2.1更新於 Oct 29, 2026

RunAPI MCP server for Gemini TTS: create tasks, poll status, check pricing.

已驗證STDIO僅桌面媒體與設計AI 與機器學習

概覽

AI 產生的概覽

RunAPI 的 Gemini TTS MCP 伺服器,讓助理建立文字轉語音任務、查詢任務狀態並查看價格。

可以做什麼
  • 建立 Gemini TTS 文字轉語音任務,可選擇等待任務進入終態,並回傳任務 ID、狀態與輸出連結
  • 查詢既有任務的目前狀態與最新結果資料
  • 在送出前查詢 Gemini TTS 模型系列的 RunAPI 價格
  • 透過瀏覽器登入流程完成 RunAPI 驗證,並把 API 金鑰寫入共用設定檔
適用情境
適合希望助理透過 RunAPI 的 Gemini TTS 模型產生語音,且只限定在這條模型系列上的情境,也包括先查價再決定是否產生。若需要存取 RunAPI 的全部模型系列,應改用更完整的 RunAPI 伺服器。
執行需求
透過 npx 從 npm 套件以 stdio 方式在本機執行,需要 Node.js。建立任務與查詢狀態需要 RunAPI 帳號:可用 login 工具走瀏覽器流程寫入 ~/.config/runapi/config.json,或在無介面主機上設定 RUNAPI_API_KEY 環境變數。查詢價格不需登入。
安裝前請注意
建立任務會在 RunAPI 帳號上產生費用,昂貴或批次請求前應先確認成本。login 工具會把 API 金鑰寫入本機設定檔,請勿將該檔案或 RUNAPI_API_KEY 的值提交到版本庫。建立任務與輪詢會把提示內容與任務資料傳送到 RunAPI 服務。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Gemini Tts Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

RunAPI Gemini TTS MCP Server

Gemini TTS API access for AI agents: run audio generation operations, poll asynchronous results, and check pricing through one focused MCP server.

Works with Claude Code, Codex, Cursor, Windsurf, VS Code, Roo Code, and any MCP-compatible host.

[npm version] [GitHub repository] [Apache-2.0 license] [MCP Server] [2 models]

Install | Tools | Models | Agent Prompts | Configuration | Links


Why This Package?

@runapi.ai/gemini-tts-mcp is a focused Model Context Protocol server for the Gemini TTS model line on RunAPI. It gives MCP-compatible assistants direct access to 1 endpoint and 2 model variants without loading the full RunAPI catalog.

Use this per-model server when an agent should stay scoped to Gemini TTS. Use @runapi.ai/mcp when one assistant should discover every RunAPI model line.


Install

Add it to Claude Code:

bash
claude mcp add gemini-tts -s user -- npx -y @runapi.ai/gemini-tts-mcp

Use project scope when the server should be shared with a repository:

bash
claude mcp add gemini-tts -s project -- npx -y @runapi.ai/gemini-tts-mcp

Codex, Cursor, Windsurf, VS Code, Roo Code, and other MCP hosts can use the same stdio command:

json
{  "mcpServers": {    "gemini-tts": {      "command": "npx",      "args": ["-y", "@runapi.ai/gemini-tts-mcp"]    }  }}

check_pricing works before sign-in. For task creation and status polling, ask your assistant to call the login tool. It opens a browser login and saves credentials to ~/.config/runapi/config.json, the same file used by runapi login. Headless and CI hosts can still set RUNAPI_API_KEY before starting the MCP host.

Ready-made examples are in examples/ for Claude, Cursor, Windsurf, VS Code, and Roo Code.


Tools

ToolAuthPurpose
text_to_speechYesCreate a Gemini TTS text to speech task and optionally wait for a terminal status. Returns the task id, status, and output URLs.
get_taskYesFetch the current status and latest payload for an existing task.
check_pricingNoLook up current pricing for a Gemini TTS model and endpoint.

Models

Gemini TTS covers 2 model variants across 1 endpoint. Each tool accepts the models listed for it:

ToolModels
text_to_speechgemini-2.5-pro-tts, gemini-3.1-flash-tts

Model availability can change between releases. Use check_pricing or the Gemini TTS model page for the current catalog view.


Agent Prompts

Ask your assistant in natural language; it can inspect pricing, create the task, and return the task id plus output URLs.

Create a task

text
Run a Gemini TTS text to speech task with RunAPI.

The assistant can call check_pricing, then text_to_speech, and return the task id, status, and output URLs.

Submit without waiting

text
Create the task but don't wait for it to finish.

The assistant calls the create tool with wait: false and returns the task id. Check on it later with get_task.

Check pricing before creating

text
Check current Gemini TTS pricing, then create the task if it matches my request.

The assistant calls check_pricing and can link to the Gemini TTS model page for the canonical catalog entry.


Configuration

The server resolves auth in this order:

  1. RUNAPI_API_KEY environment variable, useful for headless and CI hosts
  2. ~/.config/runapi/config.json, created by the MCP login tool or runapi login
  3. No key, which still allows check_pricing

The config file is normally managed by login. A pre-provisioned headless config can use:

json
{  "apiKey": "your_runapi_key"}

Do not commit real API keys.


Links

ResourceURL
Gemini TTS model pagehttps://runapi.ai/models/gemini-tts
npm package@runapi.ai/gemini-tts-mcp
GitHub repositoryrunapi-ai/gemini-tts-mcp
RunAPI MCP overviewrunapi.ai/mcp
RunAPI docsrunapi.ai/docs

License

Licensed under the Apache License, Version 2.0.

來源:README.md,提交 3500a69

工具

4

login

Authenticate RunAPI by opening a browser PKCE login flow and saving the API key to ~/.config/runapi/config.json.

輸入參數force

text_to_speech

Create a Gemini TTS task on RunAPI (text to speech). Returns a task id, status, and output URLs.

輸入參數waitmodelscenespeakers必填timeout_mstemperaturecallback_urldialogue_turns必填sample_contextpoll_interval_ms

get_task

Fetch the current status and latest result payload for a gemini-tts task.

輸入參數actiontask_id必填

check_pricing

Look up RunAPI pricing for the gemini-tts model line.

輸入參數modelaction

版本歷史

3
  1. v0.2.1最新Oct 22, 2026
  2. v0.2.0Sep 30, 2026
  3. v0.1.1Sep 16, 2026

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