RunAPI Gemini TTS MCP Server
<h1 align="center">RunAPI Gemini TTS MCP Server</h1>
<p align="center">
<strong>Gemini TTS API access for AI agents: run audio generation operations, poll asynchronous results, and check pricing through one focused MCP server.</strong>
</p>
<p align="center">
<sub>Works with Claude Code, Codex, Cursor, Windsurf, VS Code, Roo Code, and any MCP-compatible host.</sub>
</p>
<p align="center">
<a href="https://www.npmjs.com/package/@runapi.ai/gemini-tts-mcp"><img src="https://img.shields.io/npm/v/%40runapi.ai/gemini-tts-mcp?style=flat-square&color=blue" alt="npm version"></a>
<a href="https://github.com/runapi-ai/gemini-tts-mcp"><img src="https://img.shields.io/badge/GitHub-runapi--ai%2Fgemini--tts--mcp-24292f?style=flat-square" alt="GitHub repository"></a>
<a href="LICENSE"><img src="https://img.shields.io/badge/License-Apache_2.0-blue?style=flat-square" alt="Apache-2.0 license"></a>
<img src="https://img.shields.io/badge/Type-MCP_Server-blue?style=flat-square" alt="MCP Server">
<img src="https://img.shields.io/badge/Models-2-16a34a?style=flat-square" alt="2 models">
</p>
<p align="center">
<a href="#install">Install</a> |
<a href="#tools">Tools</a> |
<a href="#models">Models</a> |
<a href="#agent-prompts">Agent Prompts</a> |
<a href="#configuration">Configuration</a> |
<a href="#links">Links</a>
</p>
---
## 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`](https://github.com/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/`](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, and output URLs. |
| `get_task` | Yes | Fetch the current status and latest payload for an existing task. |
| `check_pricing` | No | Look 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:
| 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](https://runapi.ai/models/gemini-tts) 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](https://runapi.ai/models/gemini-tts) 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
| Resource | URL |
|---|---|
| Gemini TTS model page | [https://runapi.ai/models/gemini-tts](https://runapi.ai/models/gemini-tts) |
| npm package | [@runapi.ai/gemini-tts-mcp](https://www.npmjs.com/package/@runapi.ai/gemini-tts-mcp) |
| GitHub repository | [runapi-ai/gemini-tts-mcp](https://github.com/runapi-ai/gemini-tts-mcp) |
| RunAPI MCP overview | [runapi.ai/mcp](https://runapi.ai/mcp) |
| RunAPI docs | [runapi.ai/docs](https://runapi.ai/docs) |
---
## License
Licensed under the [Apache License, Version 2.0](LICENSE).
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: authentication, creating a TTS task, fetching task status, and checking pricing. No overlap or ambiguity between them.
Most tools follow a verb_noun pattern (get_task, check_pricing), and login is a simple verb. text_to_speech is a compound noun phrase rather than verb_noun, but all are lowercase with underscores and readable.
With only 4 tools, the server is tightly scoped to the essential operations for RunAPI Gemini TTS. Each tool earns its place and the count is appropriate for the narrow domain.
Core lifecycle is covered: auth, create task, poll for results, and check pricing. Missing features like task cancellation or listing historical tasks are minor gaps that don't break the primary workflow.