saidwire-mcp
OfficialRelated Servers
Alternatives to saidwire-mcp
No user-submitted related servers found.
Related Servers
- FlicenseAqualityDmaintenanceEnables high-quality transcription and subtitle generation from local media files or URLs using Faster Whisper on local hardware. It supports automatic language detection and integration with MCP clients for seamless speech-to-text workflows.3-
- AlicenseNot gradedqualityAmaintenanceProvides MCP tools to transcribe video/audio files into text, with silence-aware chunking, optional local backends, and progress notifications.19 npmMIT
- AlicenseAqualityDmaintenanceEnables AI assistants to transcribe audio files from URLs or local paths using AssemblyAI's services, with support for speaker diarization, language detection, and asynchronous job management through a standardized MCP interface.4110 npm2MIT
- AlicenseAqualityCmaintenanceEnables MCP-capable assistants to transcribe local audio files or URLs and perform speaker diarization for Spanish and Portuguese audio, with options for speaker count hints, domain prompts, and transcript retrieval in multiple formats.49 npmMIT
- AlicenseAqualityBmaintenanceProvides local audio transcription using whisper.cpp, supporting multiple models and audio formats. Enables transcription of audio files via MCP tools with optional timestamps.374 npm3MIT
- AlicenseAqualityCmaintenanceEnables MCP clients to transcribe audio/video files locally, generate SRT subtitles, and burn captions into videos via tool calls, without a cloud API.3MIT
TDQS
Scored across 2 tools
The two tools are cleanly separated by input source: transcribe_file takes a local absolute path, transcribe_url takes a public http(s) link. An agent can pick unambiguously based on whether it has a file or a URL, and the descriptions reinforce this with explicit download/size notes.
Both tools follow the same verb_noun pattern (transcribe_file, transcribe_url) with identical argument sets. The naming is fully predictable and the shared prefix makes the pairing obvious.
Only two tools is thin for a server surface, though the domain (speech-to-text) is narrow enough that it doesn't feel bloated or arbitrary. It sits at the borderline where a single additional capability would round it out.
The core lifecycle—local file and remote URL ingestion, plus text/json/srt/vtt output and optional file saving—is well covered, with no dead ends for the primary use case. Minor gaps exist around async job status for long files, batch processing, and explicit language/model selection.