MCP 服务器

RunAPI Gemini TTS MCP Server

Enables AI agents to generate speech using Gemini TTS models, with tools for text-to-speech, task polling, and pricing checks.

README

<h1 align="center">RunAPI Gemini TTS MCP Server</h1>

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.

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:

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:

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:

{
  "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

Tool	Auth	Purpose
`text_to_speech`	Yes	Create a Gemini TTS text to speech task and optionally wait for a terminal status. Returns the task id, status, output URLs, and pricing snapshot.
`get_task`	Yes	Fetch the current status and latest payload for an existing task.
`check_pricing`	No	Look up the current pricing snapshot 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:

Tool	Models
`text_to_speech`	`gemini-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

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

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

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:

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

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

{
  "apiKey": "your_runapi_key"
}

Do not commit real API keys.

Links

Resource	URL
Gemini TTS model page	https://runapi.ai/models/gemini-tts
npm package	@runapi.ai/gemini-tts-mcp
GitHub repository	runapi-ai/gemini-tts-mcp
RunAPI MCP overview	runapi.ai/mcp
RunAPI docs	runapi.ai/docs