Skip to main content
Glama
ChanthMiao

MiMo Multimodal Understanding MCP Server

by ChanthMiao

understand_audio

Transcribe, summarize, or analyze audio content by providing a task prompt and audio file or URL.

Instructions

调用小米 MIMO 多模态模型理解音频。

何时使用:当需要转录、总结、分析音频内容时使用。 不要用于:读取音频源码或元数据,这些应使用其他工具。

Args: prompt: 音频理解任务描述,如"转录音频内容"、"总结音频要点"、"识别说话人" audio_url: 单个网络音频 URL audio_path: 单个本地音频文件路径 audio_urls: 多个网络音频 URL audio_paths: 多个本地音频文件路径 system_prompt: 可选系统提示词,用于自定义模型行为 max_tokens: 最大输出长度 (默认 8192,最大 32768)

Returns: MIMO 模型返回的音频理解结果。

支持格式:MP3,WAV,FLAC,M4A,OGG 大小限制:URL方式100MB,Base64方式50MB

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
audio_urlNo
audio_pathNo
audio_urlsNo
max_tokensNo
audio_pathsNo
system_promptNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It adds useful info like supported formats and size limits, but lacks details on idempotence, authorization, or rate limits. It does not disclose if the operation is read-only or has side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections: intent, when/not, args, returns, formats, limits. Every sentence adds value, no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all parameters, use cases, and constraints (format, size). Output schema exists, so return explanation is sufficient. Could mention asynchronous behavior or latency, but overall complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description provides detailed explanations for all 7 parameters, including examples for prompt and default for max_tokens. This adds significant meaning beyond the schema names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool invokes the MIMO multimodal model for audio understanding, with explicit use cases (transcribe, summarize, analyze). It distinguishes from siblings (understand_image, understand_video) by specifying audio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit 'when to use' and 'do not use for' sections provide clear context. However, it does not name alternative tools for the excluded use case (reading source code/metadata), though siblings are image/video tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ChanthMiao/MiMo-Multimodal-Understanding-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server