Loom Advisor

Loom Advisor

Provides tools to list, retrieve, edit, and merge Loom screen recordings.

Category
访问服务器

README

Loom Advisor

MCP server for Loom video management. Provides tools to list, retrieve, edit, and merge Loom screen recordings.

Features

  • list_recorded_videos - Retrieve a list of recorded videos with pagination and folder filtering
  • get_video - Get detailed information about a specific video
  • edit_video - Edit videos by trimming or extracting clips
  • merge_videos - Combine multiple videos into one

Installation

pip install m2ai-mcp-loom-advisor

Configuration

Required environment variables:

Variable Description
LOOM_ACCESS_TOKEN OAuth2 access token for Loom API

Optional environment variables:

Variable Description Default
LOOM_BASE_URL Loom API base URL https://api.loom.com/v1

Getting an Access Token

Loom uses OAuth2 for authentication. To obtain an access token:

  1. Register your application in the Loom Developer Portal
  2. Implement the OAuth2 authorization flow
  3. Use the returned access token in your configuration

Note: Loom's public API access may be limited. Enterprise users may have additional API capabilities. Contact Loom for API access details.

Usage with Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "loom": {
      "command": "loom-advisor",
      "env": {
        "LOOM_ACCESS_TOKEN": "your-access-token"
      }
    }
  }
}

Or run directly with Python:

{
  "mcpServers": {
    "loom": {
      "command": "python",
      "args": ["-m", "loom_mcp.server"],
      "env": {
        "LOOM_ACCESS_TOKEN": "your-access-token"
      }
    }
  }
}

Tools

list_recorded_videos

Retrieve a list of recorded videos from Loom.

Parameters:

  • limit (optional): Maximum number of videos to return (1-100, default 50)
  • offset (optional): Pagination offset (default 0)
  • folder_id (optional): Filter videos by folder ID

Example:

{
  "limit": 10,
  "offset": 0,
  "folder_id": "folder-abc"
}

get_video

Retrieve detailed information about a specific video.

Parameters:

  • video_id (required): Unique identifier for the video

Example:

{
  "video_id": "abc123"
}

edit_video

Edit a video by adding clips or trimming sections.

Parameters:

  • video_id (required): Unique identifier for the video
  • editing_details (required): Object containing edit instructions
    • trim_start: Start time in seconds to trim from beginning
    • trim_end: End time in seconds where video should end
    • clips: List of clip objects with start and end times
    • title: Optional new title for the edited video
    • description: Optional new description

Example:

{
  "video_id": "abc123",
  "editing_details": {
    "trim_start": 5,
    "trim_end": 120,
    "title": "Edited Demo"
  }
}

merge_videos

Combine multiple videos into one merged video.

Parameters:

  • video_ids (required): List of video IDs to merge (minimum 2, in order)
  • title (optional): Title for the merged video

Example:

{
  "video_ids": ["video-1", "video-2", "video-3"],
  "title": "Combined Demo"
}

Development

Running Tests

# Activate virtual environment
source venv/bin/activate

# Run tests
pytest

# Run with coverage
pytest --cov=loom_mcp --cov-report=term-missing

Code Quality

# Format and lint
ruff check src tests
ruff format src tests

# Type checking
mypy src

Project Structure

loom-mcp/
├── src/
│   └── loom_mcp/
│       ├── __init__.py
│       ├── server.py          # MCP server entry point
│       ├── clients/
│       │   ├── __init__.py
│       │   └── loom.py        # Loom API client
│       └── tools/
│           ├── __init__.py
│           ├── list_recorded_videos.py
│           ├── get_video.py
│           ├── edit_video.py
│           └── merge_videos.py
├── tests/
│   ├── __init__.py
│   ├── conftest.py
│   ├── test_loom_client.py
│   ├── test_tools.py
│   └── test_server.py
├── pyproject.toml
├── README.md
└── .env.example

License

MIT


Generated by GRIMLOCK MCP Factory

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选