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 账号 runapi-builder 发布v0.2.1更新于 Oct 29, 2026
RunAPI MCP server for Gemini TTS: create tasks, poll status, check pricing.
RunAPI 的 Gemini TTS MCP 服务器,让助手创建文本转语音任务、查询任务状态并查看价格。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
参照 仓库 中的启动说明。
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.
来源: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已满足适用检查项的 90%
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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"}