/delive-transcript-analyzer

name: delive-transcript-analyzer
description: "Analyze, summarize, and extract insights from DeLive transcription sessions. Use when: user mentions DeLive, transcription, meeting transcripts, live captions, audio transcription, AI correction, corrected transcript, or transcript analysis; user wants to search, retrieve, summarize, correct, or process recorded transcripts; user asks about meeting notes, action items, discussion summaries, or transcript quality from DeLive. Requires DeLive app running locally with its MCP server or REST API."

DeLive Transcript Analyzer

Analyze and extract insights from real-time transcription sessions captured by DeLive, a desktop app for live speech-to-text.

Prerequisites

• **DeLive** must be running locally (REST API at `http://localhost:23456`)
• For MCP integration, the DeLive MCP server must be configured (see Setup below)

Setup

Option A: MCP Server (recommended for Claude Desktop / Claude Code)

The DeLive MCP server provides direct tool access. Add to your MCP config:

{
  "mcpServers": {
    "delive": {
      "command": "node",
      "args": ["<PATH_TO_DELIVE>/mcp/delive-mcp-server.js"]
    }
  }
}

Option B: REST API (for any client)

DeLive exposes a local REST API when running:

• Base URL: `http://localhost:23456/api/v1/`
• WebSocket live stream: `ws://localhost:23456/ws/live`

Available Tools (via MCP)

| Tool | Purpose | |------|---------| | `search_transcripts` | Find sessions by keyword in title or transcript content | | `get_session` | Full session with transcript, corrected transcript, AI summary, mind map, Q&A | | `get_session_transcript` | Transcript text + corrected transcript (when available) | | `get_session_summary` | AI summary, action items, keywords, mind map | | `get_recording_status` | Check if DeLive is currently recording | | `list_topics` | List topic categories for organizing sessions | | `list_tags` | List all tags used to label sessions |

Available Resources (via MCP)

| Resource URI | Description | |-------------|-------------| | `delive://sessions/recent` | Most recent 10 sessions (metadata) | | `delive://status` | Current app and recording status |

Workflow Patterns

Pattern 1: Meeting Summary to Email Draft

1. Search for the relevant meeting: `search_transcripts("weekly standup")` 2. Get the full session: `get_session("<session_id>")` 3. Use the transcript and AI summary to draft a follow-up email

Pattern 2: Lecture Notes to Study Guide

1. Find the lecture: `search_transcripts("machine learning lecture")` 2. Get the transcript: `get_session_transcript("<session_id>")` 3. Extract key concepts, create flashcards, or generate a structured study guide

Pattern 3: Code Discussion to Implementation

1. Search for the discussion: `search_transcripts("refactor database layer")` 2. Get session details: `get_session("<session_id>")` 3. Extract technical decisions and action items from the summary 4. Generate implementation code based on the discussed approach

Pattern 4: Multi-Session Analysis

1. Search broadly: `search_transcripts("project alpha")` 2. Retrieve summaries for each matching session 3. Synthesize a cross-session report: timeline, decisions made, open items

Pattern 5: Best-Quality Transcript

1. Get the transcript: `get_session_transcript("<session_id>")` 2. Check if a corrected transcript is present (returned as a separate section) 3. Prefer the corrected version for downstream processing (summaries, translations, reports)

Pattern 6: Real-Time Monitoring

Connect to the live WebSocket for real-time transcript access:

import asyncio
import websockets
import json

async def monitor():
    async with websockets.connect("ws://localhost:23456/ws/live") as ws:
        async for message in ws:
            data = json.loads(message)
            if data["type"] == "transcript":
                print(data["stableText"])

asyncio.run(monitor())

REST API Reference

All endpoints return JSON. Base URL: `http://localhost:23456`

| Method | Endpoint | Description | |--------|----------|-------------| | GET | `/api/v1/health` | Server health and version | | GET | `/api/v1/sessions` | List sessions (params: `search`, `limit`, `offset`, `topicId`, `status`) | | GET | `/api/v1/sessions/:id` | Full session detail | | GET | `/api/v1/sessions/:id/transcript` | Transcript text + corrected transcript | | GET | `/api/v1/sessions/:id/summary` | AI summary and mind map | | GET | `/api/v1/topics` | All topics | | GET | `/api/v1/tags` | All tags | | GET | `/api/v1/status` | Recording state and app info |

Tips

• **Search is case-insensitive** and matches both title and transcript content
• Sessions with `status: "completed"` have full transcripts; `"recording"` means in-progress
• The `hasSummary` field in session listings indicates whether AI post-processing has been run
• Use `limit` and `offset` for pagination when there are many sessions
• The live WebSocket at `/ws/live` broadcasts both transcript updates and session lifecycle events (`session-start`, `session-end`)
• **Corrected transcript**: `get_session_transcript` returns a `correctedTranscript` field when AI correction has been applied. Prefer this over the raw transcript for higher accuracy
• **get_session** includes a `Corrected Transcript` section when available — use it for summaries, reports, and analysis

Error Handling

If DeLive is not running, all API calls will fail with a connection error. Check: 1. DeLive app is open and running 2. The built-in server is active (check `http://localhost:23456/api/v1/health`) 3. For MCP: the MCP server process can reach DeLive on localhost