MCP Desktop DVR

Overview

The MCP Desktop DVR server is a production‑ready solution that lets AI assistants such as Claude capture, store, and analyze screen activity on macOS. By maintaining a 30‑minute rolling buffer of desktop frames, it gives Claude the ability to look back at recent visual events—whether debugging a UI bug, reviewing a code walkthrough, or monitoring a live stream—without the need for manual screenshots. This capability bridges the gap between AI reasoning and real‑time visual context, enabling assistants to answer questions about what’s on the screen or to diagnose issues that arise during a session.

At its core, the server offers a set of intuitive tools: starting or stopping continuous capture, querying the current recording state, and extracting specific time segments for analysis. When a user asks Claude to “analyze the last 30 seconds,” the server slices the buffered video into manageable segments, selects the most suitable analyzer (OpenAI GPT‑4o Vision, Tarsier2‑7B, or OCR), and streams the results back to the assistant. This tiered fallback strategy ensures that even if a cloud key is missing or an internet connection is unavailable, the assistant can still provide useful insights using local resources.

Key capabilities include:

• High‑fidelity visual analysis powered by GPT‑4o Vision, which delivers the most accurate interpretation of complex workflows and UI states.
• Local AI fallback with Tarsier2‑7B, leveraging Metal Performance Shaders for privacy‑first processing without external API calls.
• Granular time extraction that allows precise querying of any 30‑minute window, making it ideal for auditing or debugging sessions.
• Window‑specific capture so that only the relevant application’s activity is recorded, reducing noise and storage overhead.
• Robust testing and production readiness, ensuring reliable operation in real‑world scenarios.

Developers can integrate this server into their AI pipelines by adding it to the Claude Desktop configuration. Once running, the assistant can invoke the capture tools directly from natural language prompts—e.g., “Start desktop recording,” “What errors are on my screen?” or “Analyze the last 30 seconds.” The server’s output can then feed into downstream processes, such as generating documentation snippets from UI states or triggering automated test suites based on observed screen changes.

In summary, the MCP Desktop DVR transforms a static AI assistant into an interactive observer of the user’s desktop. By combining continuous capture, intelligent analysis, and seamless integration with Claude, it empowers developers to build more contextually aware applications, automate visual testing, and provide richer, real‑time assistance without compromising privacy or requiring complex infrastructure.