login
Authenticate RunAPI by opening a browser PKCE login flow and saving the API key to ~/.config/runapi/config.json.
force
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.
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。
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。
參照 儲存庫 中的啟動說明。
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
@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.
Add it to Claude Code:
Use project scope when the server should be shared with a repository:
Codex, Cursor, Windsurf, VS Code, Roo Code, and other MCP hosts can use the same stdio command:
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.
Gemini TTS covers 2 model variants across 1 endpoint. Each tool accepts the models listed for it:
Model availability can change between releases. Use check_pricing or the Gemini TTS model page for the current catalog view.
Ask your assistant in natural language; it can inspect pricing, create the task, and return the task id plus output URLs.
The assistant can call check_pricing, then text_to_speech, and return the task id, status, and output URLs.
The assistant calls the create tool with wait: false and returns the task id. Check on it later with get_task.
The assistant calls check_pricing and can link to the Gemini TTS model page for the canonical catalog entry.
The server resolves auth in this order:
RUNAPI_API_KEY environment variable, useful for headless and CI hosts~/.config/runapi/config.json, created by the MCP login tool or runapi logincheck_pricingThe config file is normally managed by login. A pre-provisioned headless config can use:
Do not commit real API keys.
Licensed under the Apache License, Version 2.0.
來源:README.md,提交 3500a69
Authenticate RunAPI by opening a browser PKCE login flow and saving the API key to ~/.config/runapi/config.json.
forceCreate a Gemini TTS task on RunAPI (text to speech). Returns a task id, status, and output URLs.
waitmodelscenespeakers必填timeout_mstemperaturecallback_urldialogue_turns必填sample_contextpoll_interval_msFetch the current status and latest result payload for a gemini-tts task.
actiontask_id必填Look up RunAPI pricing for the gemini-tts model line.
modelaction已滿足適用檢查項的 90%
該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。
請在註冊中心條目中宣告憑證請求標頭,或保持端點能夠回應探測,以便判定其認證方式。
claude mcp add gemini-tts -s user -- npx -y @runapi.ai/gemini-tts-mcpclaude mcp add gemini-tts -s project -- npx -y @runapi.ai/gemini-tts-mcp{ "mcpServers": { "gemini-tts": { "command": "npx", "args": ["-y", "@runapi.ai/gemini-tts-mcp"] } }}Run a Gemini TTS text to speech task with RunAPI.Create the task but don't wait for it to finish.Check current Gemini TTS pricing, then create the task if it matches my request.{ "apiKey": "your_runapi_key"}