# Ximilalaxiang Delive Delive

> DeLive Transcript Analyzer

- Skill: `tomevault-io/ximilalaxiang-delive-delive` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/ximilalaxiang-delive-delive`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/ximilalaxiang-delive-delive/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/ximilalaxiang-delive-delive

---


# 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:

```json
{
  "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:

```python
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

---
> Source: [XimilalaXiang/DeLive](https://github.com/XimilalaXiang/DeLive) — distributed by [TomeVault](https://tomevault.io).
<!-- tomevault:4.0:skill_md:2026-06-24 -->