---
title: "Reconstructed Slides: The rise of the agentic economy on the shoulders of MCP — Jan Curn, Apify"
category: "slides"
video_id: "blW-lSd5CYQ"
sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"]
---

# Reconstructed Slides: The rise of the agentic economy on the shoulders of MCP — Jan Curn, Apify

## Source Video
[The rise of the agentic economy on the shoulders of MCP — Jan Curn, Apify](https://www.youtube.com/watch?v=blW-lSd5CYQ)

## Method
This deck is reconstructed from the existing video frame captures by detecting likely slide regions with OpenCV, cropping/upscaling those regions, deduplicating similar crops, and OCRing the cropped slide images locally. It is a cleaner companion to the full-stage frame deck.

## Reconstructed Slides
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-001.jpg]]

- Source frame: `slide-001.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `160.13`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-002.jpg]]

- Source frame: `slide-002.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `177.17`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-003.jpg]]

- Source frame: `slide-003.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.02`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-004.jpg]]

- Source frame: `slide-004.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `174.11`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-005.jpg]]

- Source frame: `slide-005.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `174.36`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-006.jpg]]

- Source frame: `slide-006.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `170.91`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-007.jpg]]

- Source frame: `slide-007.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `167.22`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-008.jpg]]

- Source frame: `slide-008.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `164.79`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-009.jpg]]

- Source frame: `slide-009.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `168.61`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-010.jpg]]

- Source frame: `slide-010.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.53`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-011.jpg]]

- Source frame: `slide-011.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `158.32`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-012.jpg]]

- Source frame: `slide-012.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.1`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-013.jpg]]

- Source frame: `slide-013.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `165.07`
![[assets/reconstructed-slides/blW-lSd5CYQ/slide-014.jpg]]

- Source frame: `slide-014.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `163.75`
## Dense Scene-Detected Slide Candidates
- [[youtube-blW-lSd5CYQ-dense-slides]]