AssemblyAI MCP Server
Related Servers
Alternatives to AssemblyAI MCP Server
No user-submitted related servers found.
Related Servers
- 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.44 npmMIT
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to submit and manage durable long-form audio transcription jobs, and read or export structured transcripts via MCP tools.1MIT
- FlicenseAqualityCmaintenanceEnables an assistant to transcribe video or podcast recordings, then read, search, summarize, and manage the resulting transcripts through MCP tools.10-
- AlicenseAqualityBmaintenanceEnables AI assistants to transcribe audio and video from URLs or local files with high accuracy, speaker diarization, 119 languages, and word-level timestamps, while also supporting transcription management and caption export in SRT, WebVTT, or plain text.1488 npm11MIT

@speechweave/mcpofficial
AlicenseAqualityBmaintenanceMCP server for SpeechWeave transcription, enabling AI assistants to transcribe local files and URLs via wait-first or async tools.6213 npmMIT- FlicenseNot gradedqualityDmaintenanceA Model Context Protocol (MCP) server that gives AI agents the ability to process audio files — transcribe speech to text, detect spoken languages, and extract audio metadata.1-
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: get_transcript retrieves existing results, submit_transcription initiates async transcription, transcribe_file handles local files, and transcribe_url handles remote URLs. There is no overlap or ambiguity between these operations.
All tools follow a consistent verb_noun pattern with snake_case naming (e.g., get_transcript, submit_transcription, transcribe_file, transcribe_url). The naming is predictable and uniform throughout the set.
With 4 tools, the count is reasonable for a transcription service, covering core operations. It might benefit from additional tools like listing transcripts or checking status, but it's well-scoped for basic functionality.
The tools cover key transcription workflows: submitting audio, transcribing from different sources, and retrieving results. Minor gaps exist, such as no tool for listing or deleting transcripts, but agents can work effectively with the provided set.