Video to Text MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TEMP_DIR | No | 指定临时文件目录(默认:系统临时目录) | |
| WHISPER_MODEL | No | 指定 Whisper 模型(可选值:tiny, base, small, medium, large) | base |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| video_to_textB | Download a video from URL, extract audio, transcribe to text, and save locally |
| voice_to_textC | Download an audio file from URL and transcribe to text |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have distinct primary purposes: video_to_text handles video files with audio extraction, while voice_to_text handles audio files directly. However, there is some functional overlap in the transcription step, which could cause minor confusion if an agent needs to transcribe audio from a video but chooses the wrong tool. The descriptions help clarify the difference.
Both tools follow a consistent snake_case naming pattern with a clear 'source_to_text' structure (video_to_text and voice_to_text). This makes them predictable and easy to understand, with no deviations in style or convention across the set.
With only 2 tools, the server feels thin for a video-to-text domain, as it lacks operations for managing transcripts (e.g., editing, saving in different formats) or handling video/audio metadata. While the core functionality is covered, the set is borderline minimal and may limit agent workflows.
The tools cover the basic transcription process from video and audio sources, but there are notable gaps: no tools for updating, deleting, or listing transcripts, and no support for batch processing or different output formats. This could lead to dead ends in more complex agent tasks, though simple transcription needs are met.