MCP for screen recording: give Claude and Cursor your video library

The Model Context Protocol (MCP) is the open standard that lets AI assistants use tools: read files, query databases, call APIs. Most screen recording tools predate it, which is why your recordings are invisible to your AI. Hours of explained decisions, demos, and bug walkthroughs that Claude simply cannot see.

Rec ships MCP-native. One server, 18 tools, two ways to connect: a local package for Claude Code and Cursor (npx -y @recapp/mcp with a scoped API key), or the hosted endpoint with OAuth 2.1 for browser-based clients.

What your assistant can do once connected

• •Search the library. search_recordings runs semantic search across every transcript. “The demo where we showed the export flow” works even if nobody said those words.
• •Read any recording. get_transcript returns the full transcript with speaker labels, and get_summary returns the AI summary with key timestamps. Your agent can quote a recording in a ticket, a doc, or an answer.
• •Record, by itself. record_start launches a real browser with video capture. The agent navigates with browser_click and browser_type, annotates steps with record_note, and record_stop returns a share link with an AI voiceover.

Why this beats a REST API for AI workflows

Rec has a REST API too, plus webhooks and Zapier. But MCP is what makes the workflows conversational. You do not write a script to find a recording. You ask. “What did we decide about auth in last week's walkthrough?” becomes a tool call, a transcript read, and an answer with timestamps, inside the assistant you already use.

The part nothing else handles: logins

Recording public pages is easy. Real products live behind logins, and you should never paste credentials into a prompt. Rec's authenticate tool opens a visible browser window where you sign in once. The session persists in a local profile and gets reused on future recordings. The agent detects login walls and asks. It never sees a password.