Cavalry MCP Bridge

Cavalry MCP Bridge

Enables AI assistants to control Cavalry, a procedural 2D motion graphics application, through natural language commands for creating and animating scenes.

Category
访问服务器

README

Cavalry Motion App MCP Bridge

A Model Context Protocol (MCP) server that connects AI assistants (like Claude Desktop, Antigravity, Cursor, and ChatGPT) directly to Cavalry, the procedural 2D motion graphics and animation application by Scene Group.


Features

  • Procedural Layer Creation: Create shapes, text, duplicators, grids, noise generators, color palettes, math nodes, deformers, and particle emitters via natural language.
  • Dynamic Node Graph Connections: Connect outputs and inputs between nodes (e.g. wire a noise generator to a shape's scale or rotation).
  • Attribute Control & Keyframing: Inspect and update any property, scrub the timeline, and add animated keyframes.
  • Scene Introspection: Query active composition metadata, layer hierarchies, and selected nodes.
  • Render Pipeline: Add compositions to the Render Queue and trigger batch renders.
  • Raw Script Execution: Execute arbitrary JavaScript against Cavalry’s native api.* module.

Architecture

┌─────────────────────────┐          stdio (MCP)         ┌─────────────────────────────────┐
│ AI Assistant / LLM      │ ◄──────────────────────────► │ Cavalry MCP Server              │
│ (Claude, Antigravity)   │                              │ (TypeScript / Node.js)          │
└─────────────────────────┘                              └────────────────┬────────────────┘
                                                                          │
                                                             HTTP POST    │ (http://127.0.0.1:8080)
                                                                          ▼
                                                         ┌─────────────────────────────────┐
                                                         │ In-Cavalry Script Bridge        │
                                                         │ (MCPBridge.js in Scripts menu)  │
                                                         │ ───► api.create(...)            │
                                                         │ ───► api.set(...)               │
                                                         │ ───► api.connect(...)           │
                                                         └─────────────────────────────────┘

Quick Start

1. Install Dependencies & Build

From this project directory:

npm install
npm run build

2. Install Bridge Script into Cavalry

Run the installer to copy MCPBridge.js to your Cavalry scripts folder:

npm run install-bridge

On Windows, this copies MCPBridge.js to %APPDATA%\Cavalry\Scripts\.

3. Start the Bridge in Cavalry

  1. Launch Cavalry.
  2. Go to the top menu: Scripts → MCPBridge.
  3. A small panel will open showing Status: Online (Port 8080). Keep this open while using the MCP server.

(Alternatively, if you already have the Stallion extension active, it also listens on port 8080 and works seamlessly with this MCP server).

4. Test the Connection

Verify that the MCP server can communicate with Cavalry:

npm run test-connection

MCP Client Configuration

Claude Desktop

Add the following to your claude_desktop_config.json (located at %APPDATA%\Claude\claude_desktop_config.json on Windows or ~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "cavalry": {
      "command": "node",
      "args": [
        "C:/Users/david/Documents/ANTIGRAVITY APP/CALVARY MCP/dist/index.js"
      ],
      "env": {
        "CAVALRY_BRIDGE_PORT": "8080"
      }
    }
  }
}

Antigravity / Cursor / Custom Client

Add to your settings or .cursor/mcp.json:

{
  "mcpServers": {
    "cavalry": {
      "command": "node",
      "args": ["C:/Users/david/Documents/ANTIGRAVITY APP/CALVARY MCP/dist/index.js"]
    }
  }
}

Available MCP Tools

Tool Description
cavalry_run_script Run arbitrary JavaScript code in Cavalry using api.*.
cavalry_eval_expression Evaluate a single expression and return its value.
cavalry_get_scene_info Query active composition name, frame count, FPS, and layer count.
cavalry_get_comp_layers List all layer IDs in the current composition.
cavalry_get_selected_layers Get the IDs of currently selected layers.
cavalry_create_layer Create a new layer/node (basicShape, textShape, duplicator, etc.).
cavalry_set_attributes Set one or more attribute values on a layer.
cavalry_get_attributes Query an attribute value on a layer.
cavalry_delete_layer Delete a layer/node from the scene.
cavalry_connect_attributes Connect source attribute to target attribute in dependency graph.
cavalry_disconnect_attributes Disconnect an attribute connection.
cavalry_set_frame Scrub the playhead to a specific frame.
cavalry_get_frame Get the current frame number.
cavalry_set_keyframe Add a keyframe with value at a specified frame.
cavalry_playback_control Play, stop, or rewind the timeline.
cavalry_add_to_render_queue Add the composition to the Render Manager.
cavalry_render_queue Start rendering items in the queue.

Example Prompts for AI Assistants

1. Animated Noise Grid

"Create a 12x12 grid of rounded squares in Cavalry, attach a noise modifier to their rotation and scale, and set the fill color to electric blue."

2. Kinetic Typography

"Create kinetic text with the headline 'ANTIGRAVITY' in Cavalry. Set the font size to 120, center it, and add a bouncy spring oscillation to the Y position."

3. Radial Burst Animation

"Build a radial burst animation with 24 lines radiating outwards from the center, driven by a step duplicator and keyed to expand from frame 0 to frame 45."


License

MIT

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