Can I save extracted Loom content to my local disk?

Yes, many of the 'read' tools accept an optional `save_dir` parameter, allowing you to save content like transcripts, summaries, and metadata directly to your local file system on demand.

What is the Loom MCP Server?

The Loom MCP Server integrates Loom's internal GraphQL API with AI clients like Claude and Cursor, providing 59 tools for comprehensive video content management and extraction.

How do I authenticate the Loom MCP Server?

Authentication is done by grabbing the `connect.sid` session cookie from your browser's Loom.com session and providing it as an environment variable (LOOM_COOKIE) in your MCP client configuration.

What kind of Loom video content can I access and manage?

You can access detailed video metadata, transcripts, captions, AI summaries, chapters, key takeaways, comments, tasks, and reactions. You can also organize your Loom content by managing folders, spaces, and watch lists.

What AI clients are compatible with this Loom integration?

This integration is designed to work seamlessly with Claude Desktop, Claude Code, Cursor, VS Code, and any other client that supports the Model Context Protocol (MCP).

Loom

Name: Loom
Author: karbassi

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Integrate Loom's internal GraphQL API with AI clients like Claude and Cursor, exposing 59 tools for comprehensive video management and content extraction.

Loom

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Integrate Loom's internal GraphQL API with AI clients like Claude and Cursor, exposing 59 tools for comprehensive video management and content extraction.

Loom provides an MCP (Model Context Protocol) server designed to bridge the powerful capabilities of Loom's video platform with AI-compatible clients. This server allows users to programmatically interact with their Loom content, enabling AI agents to list, search, and retrieve detailed information about videos, including transcripts, AI-generated summaries, chapters, and key takeaways. Beyond content consumption, it offers tools for managing video settings, comments, tasks, reactions, and organizing videos within folders and spaces, enhancing productivity by bringing Loom directly into AI-driven workflows.

主な機能

01Save fetched content (transcripts, summaries, etc.) directly to disk on demand.

02Organize Loom content by creating and managing folders, spaces, and watch lists.

03Access detailed video metadata, transcripts, captions, AI summaries, chapters, and key takeaways.

043 GitHub stars

05Perform AI-powered semantic search across Loom videos and retrieve related content.

06Manage video interactions like comments, tasks, reactions, and tags.

ユースケース

01Enable conversational AI to search for and retrieve specific information from Loom videos or user profiles.

02Automate the summarization and analysis of Loom videos using an LLM.

03Integrate Loom video management (e.g., updating settings, moving videos) into AI-driven productivity workflows.