get_note_transcript

Overview

Last resort. Transcripts are token-heavy (a 1-hour meeting can exceed 30K tokens). Try search_notes first — it returns curated documents (one-pager, custom) that are typically 10× more compact and equally informative. Use this tool only when you need exact transcribed words for a direct quote.

get_note_transcript returns the full transcript of a note with timestamps, plus note metadata. HTML is stripped from each paragraph; the response carries both a structured paragraphs array (programmatic use) and a pre-formatted transcription string (direct LLM consumption). Primary Use Cases:

Quoting exact words spoken in the meeting.
Slicing the transcript by time range using the structured paragraphs array.
Analyzing conversation context when documents don’t capture the wording you need.

Key Features:

Full transcript with [HH:MM:SS]-prefixed lines.
Structured paragraphs[] with timeFrom / timeTo / text for time-based filtering.
HTML is stripped before output (sanitized at the MCP layer).

Parameters

Parameter	Type	Required	Description
`noteGuid`	string	Yes	Unique note identifier

noteGuid (required)

The unique identifier of the note to retrieve. Example:

{
  "noteGuid": "abc-123-def"
}

How to Get Note GUID:

Use list_notes (lightweight) to find candidates by folder, date, or keyword.
Use the noteGuid from the result. If you also need document content for context, fetch it via search_notes first; only fall back to this tool when verbatim spoken words are required.

Response Format

Success Response

{
  "noteGuid": "abc-123-def",
  "title": "Weekly Team Meeting",
  "participants": ["Alice Kim", "Bob Park"],
  "createdAt": "2024-01-15T10:30:00Z",
  "recordingDurationSeconds": 3625,
  "paragraphs": [
    {
      "timeFrom": "2024-01-15T10:30:05Z",
      "timeTo":   "2024-01-15T10:30:18Z",
      "text": "Let's start with the project update."
    },
    {
      "timeFrom": "2024-01-15T10:30:18Z",
      "timeTo":   "2024-01-15T10:30:35Z",
      "text": "Sure, I've completed the migration..."
    }
  ],
  "transcription": "[10:30:05] Let's start with the project update.\n[10:30:18] Sure, I've completed the migration...",
  "totalParagraphs": 87
}

Field Descriptions:

Field	Type	Description
`noteGuid`	string	Unique note identifier.
`title`	string	Note title.
`participants`	string[]	Participant names (or emails when names are unavailable).
`createdAt`	string	ISO 8601 creation timestamp.
`recordingDurationSeconds`	number	Recording length in seconds.
`paragraphs[]`	array	Structured paragraphs (programmatic use).
`paragraphs[].timeFrom`	string \| null	ISO 8601 start time of the paragraph.
`paragraphs[].timeTo`	string \| null	ISO 8601 end time of the paragraph.
`paragraphs[].text`	string	HTML-stripped paragraph text.
`transcription`	string	Pre-formatted markdown-friendly string with `[HH:MM:SS]` prefixes (UTC). Lines joined with `\n` (single newline).
`totalParagraphs`	number	Number of paragraphs returned.

Two formats, same data. paragraphs[] is for programmatic slicing (e.g., “give me everything between 10:30 and 10:45”). transcription is for direct LLM consumption — paste it in and let the model read. Don’t double-load both unless you need both views.

Delimiter change. The transcription string now joins paragraphs with a single \n (was previously \n\n). Callers that split by double-newline to recover paragraph boundaries should switch to the structured paragraphs[] array.

Usage Examples

Example 1: Basic Usage

AI Request:

Show me the full transcript of meeting abc-123-def

MCP Call:

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "get_note_transcript",
    "arguments": {
      "noteGuid": "abc-123-def"
    }
  },
  "id": 1
}

Response:

{
  "jsonrpc": "2.0",
  "result": {
    "noteGuid": "abc-123-def",
    "title": "Q4 Marketing Strategy Meeting",
    "participants": ["Sarah Kim", "John Park"],
    "createdAt": "2025-11-10T10:00:00Z",
    "transcription": "Sarah Kim: Welcome to the Q4 marketing strategy meeting.\n\nJohn Park: Thanks. Let me present our website analytics...\n\n..."
  },
  "id": 1
}

Example 2: Progressive Disclosure Pattern

Step 1: Search

Find recent marketing meetings

Uses search_notes - Fast (~1 second, ~100 tokens) Step 2: Summary

What was discussed in meeting abc-123-def?

Uses get_note_summary - Medium (~2 seconds, ~500 tokens) Step 3: Full Transcript (Only if Needed)

Show me the exact conversation about budget allocation

Uses get_note_transcript - Slow (~5 seconds, ~4,000 tokens)

Token Usage

Typical Meeting (1 hour): ~3,000-5,000 tokens Comparison (3-tier discovery):

Tool	Token Usage	When to Use
`list_notes`	~50 tokens per note	Finding which notes exist (metadata only)
`search_notes`	~1,500 tokens per note	Reading the content behind a topic (returns documents)
`get_note_transcript`	~3,000-5,000 tokens per hour	Last resort — exact spoken words for quoting
`get_note_summary`	~200-800 tokens	Quick AI summary of one note
`get_note_document`	~300-2,000 tokens	Specific generated document

Token SavingsTry search_notes first — its document output is typically 10× more compact than the raw transcript and answers most “what did the team decide” questions. Only reach for get_note_transcript when you genuinely need verbatim wording.

Best Practices

Use Progressive Disclosure (3-tier)

Always follow this order:

list_notes — find which notes exist (~50 tokens per note)
search_notes — read the documents for a matched topic (~1,500 tokens per note)
get_note_transcript — only if exact wording is required (~4,000 tokens per hour)

Most “what did we decide?” questions stop at step 2. This saves up to 90% of tokens compared to jumping straight to transcripts.

When to Use Transcripts

Use full transcripts when you need to:

Find exact quotes or statements
Analyze detailed conversation flow
Understand complete context
Reference specific discussions

Don’t use transcripts for:

Quick overview (use summary instead)
Action items (use get_note_document)
General understanding (use summary)

Handle Large Transcripts

For very long meetings (2+ hours):

Expect 5,000-10,000 tokens
May cause timeout (60 seconds)
Consider requesting specific sections via summary first
Use summary to identify relevant parts before loading full transcript

Common Errors

Missing Note GUID

Solution: Provide the noteGuid parameter.

Note Not Found

Possible Causes:

Note doesn’t exist
Note has been deleted
You don’t have access to this note

Solution: Verify the note GUID using search_notes.

Request Timeout

Causes:

Very long meeting transcript (2+ hours)
Server load

Solutions:

Use get_note_summary instead
Retry after a short delay
Contact support if problem persists

Performance

Response Time:

Meeting Length	Tokens	Response Time
30 minutes	~1,500	~2 seconds
1 hour	~3,000	~3 seconds
2 hours	~6,000	~5 seconds
3+ hours	~9,000+	~8 seconds (may timeout)

Cache BehaviorTranscripts are cached for 15 minutes. Subsequent requests for the same note will be faster.

Get Started

Fundamentals

API Reference

Webhooks

Template Based Documents

MCP Server

External Viewers

Overview

Parameters

noteGuid (required)

Response Format

Success Response

Usage Examples

Example 1: Basic Usage

Example 2: Progressive Disclosure Pattern

Token Usage

Best Practices

Common Errors

Missing Note GUID

Note Not Found

Request Timeout

Performance

Get Started

Fundamentals

API Reference

Webhooks

Template Based Documents

MCP Server

External Viewers

Documentation Index

​Overview

​Parameters

​noteGuid (required)

​Response Format

​Success Response

​Usage Examples

​Example 1: Basic Usage

​Example 2: Progressive Disclosure Pattern

​Token Usage

​Best Practices

​Common Errors

​Missing Note GUID

​Note Not Found

​Request Timeout

​Performance

Overview

Parameters

noteGuid (required)

Response Format

Success Response

Usage Examples

Example 1: Basic Usage

Example 2: Progressive Disclosure Pattern

Token Usage

Best Practices

Common Errors

Missing Note GUID

Note Not Found

Request Timeout

Performance