mcpField
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Faceless

Faceless

Remote
faceless.soMedia & Design0Updated 9w ago

About Faceless

Faceless is an extension for Claude Desktop that creates, renders and publishes AI faceless videos through Faceless.so. It requires a Faceless API key.

Key features

  1. 01Create AI faceless videos
  2. 02Render videos
  3. 03Publish videos

Use cases

  1. 01Make AI videos for YouTube
  2. 02Make AI videos for TikTok
  3. 03Make AI videos for Instagram

MCP support

This project is a Claude Desktop extension for creating, rendering and publishing videos through Faceless.so.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://faceless.so/api/v1/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Faceless for Claude Desktop

Create, render and publish AI faceless videos with Faceless.so from Claude Desktop.

Setup

  1. Install the extension and paste your Faceless API key when prompted (create one at https://faceless.so/team).
  2. Ask Claude: "Check my Faceless credits" or "Make a faceless video about deep sea creatures".

Privacy Policy

This extension sends requests only to the Faceless.so API (https://faceless.so) using the API key you provide, which is stored by Claude Desktop on your machine. Video scripts, settings and publishing instructions you provide are processed to generate and publish your videos. See the full policy for data collection, usage, storage, retention, third-party sharing and contact information: https://faceless.so/privacy

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.