Access Loom video library and transcripts from your AI coding assistant. Search videos by title or content, read full transcripts, extract key moments, and manage video sharing settings. The server enables AI-assisted video content management — your assistant can summarize video content, find specific moments by topic, generate written documentation from video walkthroughs, and help organize team knowledge captured in Loom recordings.
npx mcp-server-loomAdd the following to your client configuration file.
{
"mcpServers": {
"mcp-server-loom": {
"command": "npx",
"args": [
"-y",
"@mcp/mcp-server-loom"
]
}
}
}{
"mcpServers": {
"mcp-server-loom": {
"command": "npx",
"args": [
"-y",
"@mcp/mcp-server-loom"
]
}
}
}| Client | Status |
|---|---|
| claude-desktop | Full Support |
| cursor | Full Support |
Run the install command above or copy the configuration snippet for your preferred MCP client.
Add any required API keys or authentication tokens to your MCP client configuration. Check the GitHub README for setup details.
Once configured, the server's tools become available in your AI assistant. You can access features like video search by content and full transcript reading.
Loom Videos MCP Server is an MCP (Model Context Protocol) server created by Loom Community that allows AI coding assistants to interact with external services and data sources programmatically. Access Loom video library and transcripts from your AI coding assistant. Search videos by title or content, read full transcripts, extract key moments, and manage video sharing settings. The server enables AI-assisted video content management — your assistant can summarize video content, find specific moments by topic, generate written documentation from video walkthroughs, and help organize team knowledge captured in Loom recordings. The server communicates via the stdio transport type and is licensed under MIT.
MCP servers like Loom Videos MCP Server extend the capabilities of AI assistants beyond code generation and into real-world integrations. Instead of manually switching between your AI assistant and external tools, the MCP protocol lets the assistant call structured APIs directly — reading data, triggering actions, and maintaining context across interactions. This reduces context switching and allows developers to stay in their IDE or terminal while the assistant handles the integration layer.
With 6 documented capabilities — including video search by content, full transcript reading, key moment extraction — Loom Videos MCP Server is one of the more feature-rich MCP servers in its category. With 450 GitHub stars, the project has an active community of contributors and users.
Use Loom Videos MCP Server when you want your AI coding assistant to interact with access loom video library and transcripts from your ai coding assistant. search directly from the chat or terminal interface, without manual copy-pasting.
If you find yourself constantly switching between your AI assistant and external tools,Loom Videos MCP Server eliminates that friction. The assistant can read context, take actions, and report results — all within a single conversation thread.
MCP servers work well for semi-automated workflows where the AI handles repetitive integration tasks — fetching data, updating records, posting notifications — while you focus on higher-level decisions and code architecture.
Loom Videos MCP Server works across 2 compatible clients, including claude-desktop, cursor. This means you can use the same server configuration regardless of which AI coding tool your team prefers.
Several MCP servers offer overlapping functionality. The right choice depends on your specific integration needs, the AI clients you use, and your preference for community vs. official support. Here is how Loom Videos MCP Server compares:
Outlook MCP Server by Community is less popular by GitHub stars (280 vs 450). Both servers are maintained by different teams — evaluate documentation quality and recent commit activity when choosing.
Slack MCP Server by Anthropic is more popular by GitHub stars (18.5K vs 450). Both servers are maintained by different teams — evaluate documentation quality and recent commit activity when choosing.
Google Drive MCP Server by Anthropic is more popular by GitHub stars (18.5K vs 450). Both servers are maintained by different teams — evaluate documentation quality and recent commit activity when choosing.
Brave Search MCP Server by Anthropic is more popular by GitHub stars (18.5K vs 450). Both servers are maintained by different teams — evaluate documentation quality and recent commit activity when choosing.
Loom Videos MCP Server allows AI coding assistants like Claude Code, Cursor, and VS Code Copilot toaccess loom video library and transcripts from your ai coding assistant. search videos by title or content, read full transcripts, extract key moments, and manage video sharing settings. the server enables ai-assisted video content management — your assistant can summarize video content, find specific moments by topic, generate written documentation from video walkthroughs, and help organize team knowledge captured in loom recordings through the Model Context Protocol. Instead of manually performing these actions yourself, the AI assistant invokes server tools directly during your conversation.
Run `npx mcp-server-loom` in your terminal, or copy one of the JSON configuration snippets above into your MCP client settings file. Most clients (Claude Desktop, VS Code, Cursor) use a JSON config file — see the Configuration section for client-specific snippets.
Yes, Loom Videos MCP Server is free and open source under the MIT license. You can use it, modify it, and contribute to it via the GitHub repository. Note that while the server itself is free, the external services it connects to (such as APIs or cloud platforms) may have their own usage costs.
Loom Videos MCP Server has been tested with claude-desktop, cursor (full support). Any MCP-compatible client should work, but verify specific tool support in the client's documentation. The compatibility table above shows the latest status.
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