Skip to main content
Glama
195,884 tools. Last updated 2026-06-12 07:22

"Transcribing Voice Conversations into Structured Meeting Notes" matching MCP tools:

  • Store notes by exact name for precise later retrieval. Save structured data, meeting notes, or API documentation with unique identifiers, enabling direct access without semantic search.
    MIT
  • Transcribe audio in any of 13 languages and translate into 119 target languages with one payment. Ideal for understanding foreign voice messages or meeting recordings.
    MIT
  • Capture decisions, context, meeting notes, or blockers by creating or updating notes with markdown content and optional tags. Links notes to projects, epics, or tasks for structured tracking.
    MIT

Matching MCP Servers

  • A
    license
    -
    quality
    B
    maintenance
    MCP server providing managed persistent memory for AI agents. Read and write structured state across sessions, tools, and restarts at 1000+ requests per second, with no infrastructure to self-host or operate.
    Last updated
    2
    Apache 2.0

Matching MCP Connectors

  • Podcast directory search + best podcasts + recommendations via Listen Notes. Free key required.

  • take-the-meeting MCP — wraps StupidAPIs (requires X-API-Key)

  • Extract action items from meeting notes to identify tasks, responsibilities, and deadlines. Use note ID or meeting title to retrieve specific action items for follow-up.
    MIT
  • Retrieve complete meeting notes and transcripts in Markdown format using a meeting ID. Access organized meeting content for review and reference.
    MIT
  • Retrieve structured meeting notes including agenda items, discussion topics, and decisions from Fellow.ai meetings using note ID, recording ID, or meeting title.
    MIT
  • Poll the status of an automatic speech recognition task and retrieve the transcript with timestamps when processing completes. Returns status values: queued, downloading, transcribing, finalizing, done, or failed.
    MIT
  • Retrieve recent voice transcription corrections to analyze systematic Whisper errors, debug mis-transcriptions, or train vocabulary. Returns original and corrected text, confidence delta, timestamp, and correction source.
    AGPL 3.0
  • Create custom voice profiles from audio samples for text-to-speech and speech-to-speech applications. Analyze MP3 or WAV files to generate voice replicas that mimic original audio characteristics.
    MIT
  • Retrieve a breakdown of credit usage by feature and product scope, showing how credits are consumed across voice AI, voice models, and platform services.
    MIT