Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Open AI Text To Speech1 MCP Server Convert 'Welcome to our meeting' to audio using the Nova voice"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
用于访问 Open Ai Text To Speech1 API 的 MCP 服务器。
EMCP 是一个强大的 MCP 服务器管理平台，让您无需手动配置即可快速使用各种 MCP 服务器！
🌐 访问 EMCP 平台
📝 注册并登录账号
🎯 进入 MCP 广场，浏览所有可用的 MCP 服务器
🔍 搜索或找到本服务器（bach-open_ai_text_to_speech1）
🎉 点击 "安装 MCP" 按钮
✅ 完成！即可在您的应用中使用
✨ 零配置：无需手动编辑配置文件
🎨 可视化管理：图形界面轻松管理所有 MCP 服务器
🔐 安全可靠：统一管理 API 密钥和认证信息
🚀 一键安装：MCP 广场提供丰富的服务器选择
📊 使用统计：实时查看服务调用情况
立即访问 EMCP 平台 开始您的 MCP 之旅！
Related MCP server: MCP TTS Server
这是一个 MCP 服务器，用于访问 Open Ai Text To Speech1 API。
PyPI 包名: bach-open_ai_text_to_speech1
版本: 1.0.0
传输协议: stdio
pip install bach-open_ai_text_to_speech1pip install -e .# 运行（uvx 会自动安装并运行）
uvx --from bach-open_ai_text_to_speech1 bach_open_ai_text_to_speech1
# 或指定版本
uvx --from bach-open_ai_text_to_speech1@latest bach_open_ai_text_to_speech1python server.py# 安装
pip install bach-open_ai_text_to_speech1
# 运行（命令名使用下划线）
bach_open_ai_text_to_speech1此 API 需要认证。请设置环境变量:
export API_KEY="your_api_key_here"变量名 | 说明 | 必需 |
| API 密钥 | 是 |
| 不适用 | 否 |
| 不适用 | 否 |
编辑 Cursor MCP 配置文件 ~/.cursor/mcp.json:
{
"mcpServers": {
"bach-open_ai_text_to_speech1": {
"command": "uvx",
"args": ["--from", "bach-open_ai_text_to_speech1", "bach_open_ai_text_to_speech1"],
"env": {
"API_KEY": "your_api_key_here"
}
}
}
}编辑 Claude Desktop 配置文件 claude_desktop_config.json:
{
"mcpServers": {
"bach-open_ai_text_to_speech1": {
"command": "uvx",
"args": ["--from", "bach-open_ai_text_to_speech1", "bach_open_ai_text_to_speech1"],
"env": {
"API_KEY": "your_api_key_here"
}
}
}
}此服务器提供以下工具:
speechThe speech endpoint takes in three key inputs: the model name, the text that should be turned into audio, and the voice to be used for the audio generation.
端点: POST /
传输协议: stdio
HTTP 客户端: httpx
MIT License - 详见 LICENSE 文件。
此服务器由 API-to-MCP 工具生成。
版本: 1.0.0
The speech endpoint takes in three key inputs: the model name, the text that should be turned into audio, and the voice to be used for the audio generation.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should fully disclose behavior. It only lists inputs and contradicts the schema. No mention of output format, side effects, or limitations. The inconsistency with the schema undermines transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is factually inaccurate when compared to the schema. Conciseness is not beneficial if it leads to misrepresentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about return values or output format. Given the tool's complexity (zero defined parameters), the description fails to provide a complete picture, especially with the parameter contradiction.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema shows no parameters, yet the description claims three key inputs. This is a direct contradiction. The description does not add meaning; it misleads by asserting parameters that are not defined in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates audio from text using a model and voice, which defines the purpose well. However, it contradicts the input schema by mentioning three inputs that are not represented in the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or context. It simply describes the function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0speechScored across 1 tool
With only one tool, there is no possibility of confusion between tools.
The single tool is named with a clear noun that describes its function, but there is no verb_noun pattern to evaluate consistency.
One tool is borderline; it covers the core functionality but may not be enough for agents needing to discover available voices or models.
The tool surface lacks additional endpoints for listing voices or models, which are typical in text-to-speech services, making it incomplete for some use cases.
AI voice generation: text-to-speech and voice cloning from any MCP client.
MCP server exposing the AceDataCloud Fish Audio API (text-to-speech with voice conditioning)
MCP server for Text-to-Speech
Generate game-ready 3D models, textures, and audio from natural language, over MCP.