What file formats are supported?
glTF and GLB (both binary glTF and standard glTF) are supported.
@GeoLibra
基本信息
A comprehensive MCP server for processing, validating, optimizing, and analyzing 3D models with glTF/GLB support.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"3d-asset-processing-mcp": {
"command": "npx",
"args": [
"-y",
"3d-asset-processing-mcp"
]
}
}
}Analyze a 3D model and provide detailed statistics and recommendations
Validate a 3D model for compliance and compatibility
Execute gltf-pipeline CLI for BASIC glTF operations: glTF↔GLB conversion, embed/separate resources, glTF 1.0→2.0 upgrade, basic Draco compression, cleanup unused elements. Limited to basic file format operations and simple compression.
Execute gltf-transform CLI for ADVANCED glTF processing: Meshopt compression, Draco compression, texture compression (WebP/AVIF/JPEG/PNG), KTX2+Basis compression (ETC1S/UASTC), geometry optimization (quantize/weld/simplify/tangents), scene optimization (center/flatten/join), material conversion (metalrough/unlit), animation optimization (resample). Supports multi-step processing for complex operations.
A comprehensive MCP server for processing, validating, optimizing, and analyzing 3D models with glTF/GLB support. It provides both basic and advanced operations through integrated tools, intended for developers working with 3D assets in AI or automation workflows.
Add the server to your MCP client configuration using the npx command npx -y 3d-asset-processing-mcp@0.0.1-beta.5. All dependencies (gltf-pipeline, gltf-transform) are bundled, so no additional setup is required. The server exposes four tools: analyze_model, validate_model, gltf-pipeline-executor, and gltf-transform-executor.
glTF and GLB (both binary glTF and standard glTF) are supported.
No. All processing libraries (gltf-pipeline, gltf-transform) are included with the package.
Four tools: `analyze_model` (analysis), `validate_model` (validation), `gltf-pipeline-executor` (basic processing), and `gltf-transform-executor` (advanced processing).
Clone the repository, run `npm install` and `npm run build`, then point the MCP client to `dist/server.js` using the `node` command.
Use `npx @modelcontextprotocol/inspector` alongside the server configuration.

Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov

Model Context Protocol Servers
🚀 The fast, Pythonic way to build MCP servers and clients.
Hindsight: Agent Memory That Learns
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
评论