Can my AI generate a 3D model from a product photo with PBR textures?

Yes! Use the `generate_pbr_textures_3d` tool with your product image URL. Pixazo will generate a 3D model with complete PBR texture maps including albedo, normal, roughness, metallic, and ambient occlusion. You can specify texture resolution (1024, 2048, or 4096) and output format (GLB, OBJ, FBX). The resulting model is ready for game engines, product visualization, and e-commerce platforms with physically accurate materials.

Which model should I use for the highest quality 3D generation?

For the highest quality, use `generate_hunyuan_3d` (Hunyuan by Tencent) or `generate_hyper_3d` (Hyper3D). Both produce production-quality geometry with detailed surface reproduction. Hunyuan excels at accurate proportions and realistic details, while Hyper3D focuses on clean topology and precise texture mapping. For text-to-3D with quality control, use `generate_text_to_3d` with quality set to ultra. All models support output formats GLB, OBJ, FBX, GLTF, and USDZ.

Can I generate 3D characters with automatic rigging for animation?

Yes! Use the `generate_rigged_3d` tool with a character reference image. You can specify the rig type (humanoid, quadruped, or biped) and the API will generate a 3D model with automatic skeletal rigging including bone hierarchies and weight painting. The output is suitable for direct import into Unity, Unreal Engine, Blender, or any animation software. Output formats include FBX (recommended for rigs), GLB, and GLTF.

Pixazo 3D MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Pixazo 3D
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Pixazo 3D through Vinkius, pass the Edge URL in the `mcps` parameter and every Pixazo 3D tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Pixazo 3D Specialist",
    goal="Help users interact with Pixazo 3D effectively",
    backstory=(
        "You are an expert at leveraging Pixazo 3D tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Pixazo 3D "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Pixazo 3D MCP Server

Connect your Pixazo 3D API to any AI agent and take full control of production-quality 3D asset generation from images and text through natural conversation.

When paired with CrewAI, Pixazo 3D becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Pixazo 3D tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Hunyuan 3D — Generate high-fidelity 3D models from images with Tencent Hunyuan technology
Hyper3D — Create detailed 3D models with high-fidelity geometry and texture reproduction
Tripo3D — Fast 3D generation optimized for speed and quick previews
Trellis3D — Generate structured 3D models with clean topology for editing and animation
Text to 3D — Create 3D models directly from text descriptions with style control
Image to 3D — Convert any image to a 3D model with the optimized Pixazo pipeline
Styled 3D — Generate 3D models in specific artistic styles (photorealistic, anime, cartoon, low-poly)
Low-Poly 3D — Create optimized low-poly models for real-time games and mobile applications
Rigged 3D — Generate 3D characters with automatic skeletal rigging for animation
PBR Textures — Generate 3D models with full PBR texture maps (albedo, normal, roughness, metallic, AO)
Format Conversion — Convert 3D models between GLB, OBJ, FBX, GLTF, USDZ, 3DS, and DAE formats
Mesh Optimization — Optimize 3D meshes for performance and file size reduction

The Pixazo 3D MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Pixazo 3D to CrewAI via MCP

Follow these steps to integrate the Pixazo 3D MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Pixazo 3D

Why Use CrewAI with the Pixazo 3D MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Pixazo 3D through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Pixazo 3D + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Pixazo 3D MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Pixazo 3D for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Pixazo 3D, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Pixazo 3D tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Pixazo 3D against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Pixazo 3D MCP Tools for CrewAI (12)

These 12 tools become available when you connect Pixazo 3D to CrewAI via MCP:

convert_3d_format

Preserves geometry, textures, materials, and rigging data during conversion. Essential for pipeline integration, platform compatibility, and format standardization. AI agents should use this when users ask "convert this GLB model to FBX", "change this 3D file to USDZ for AR", or need 3D format conversion for specific platform or software requirements. Convert 3D models between different file formats

generate_hunyuan_3d

Hunyuan excels at producing detailed geometry with accurate proportions and realistic textures from single or multiple reference images. Accepts image URLs or base64 image data. Returns 3D model files with PBR textures in formats like GLB, OBJ, or FBX. Essential for product visualization, character creation, and asset generation requiring high geometric accuracy. AI agents should use this when users need production-quality 3D models from product photos, concept art, or reference images with precise detail reproduction. Generate 3D models using Hunyuan 3D model from images

generate_hyper_3d

Hyper3D produces clean mesh topology with accurate surface details, making it ideal for game assets, AR/VR content, and e-commerce product displays. Accepts image URLs and returns downloadable 3D files. Essential for applications requiring precise geometry and professional-grade output quality. AI agents should reference this when users need high-detail 3D models suitable for game engines, product showcases, or professional 3D workflows. Generate detailed 3D models using Hyper3D model

generate_image_to_3d

Accepts product photos, concept art, sketches, or any reference image and generates a corresponding 3D model. Supports multiple output formats and quality settings. Essential for e-commerce product visualization, concept art to 3D conversion, and general image-to-3D workflows. AI agents should reference this when users ask "convert this product photo to 3D", "turn this sketch into a 3D model", or need reliable general-purpose image-to-3D conversion. Convert images to 3D models using Pixazo image-to-3D pipeline

generate_lowpoly_3d

Low-poly models use minimal polygons while maintaining recognizable shape, making them ideal for performance-critical applications. Accepts reference images and returns optimized meshes with controlled polygon counts. Essential for game development, mobile applications, web-based 3D viewers, and any scenario requiring efficient 3D rendering. AI agents should reference this when users need low-poly game assets, mobile-optimized 3D models, or performance-friendly 3D content. Generate low-poly 3D models optimized for real-time applications

generate_pbr_textures_3d

PBR textures ensure realistic material appearance under any lighting condition in game engines and 3D renderers. Accepts reference images and returns 3D models with texture map sets. Essential for game asset creation, product visualization requiring realistic materials, and applications needing physically accurate rendering. AI agents should reference this when users need game-ready assets with full PBR materials, product visualizations with realistic surface appearance, or models with complete texture map sets. Generate 3D models with full PBR texture maps (albedo, normal, roughness, metallic, AO)

generate_rigged_3d

Supports character models, creatures, and articulated objects. The generated rigs include bone hierarchies and weight painting suitable for standard animation workflows. Accepts character reference images and returns rigged 3D files. Essential for game character creation, animated content pipelines, and applications requiring animation-ready 3D assets. AI agents should use this when users ask "create an animated-ready 3D character", "generate a rigged model from this character image", or need animation-ready 3D output. Generate 3D models with automatic skeletal rigging for animation

generate_styled_3d

Users provide a reference image and select the desired output style. Essential for stylized game assets, anime character creation, cartoon visualization, and artistic 3D content. AI agents should use this when users ask "create an anime-style 3D character from this image", "generate a cartoon 3D model", or need stylized 3D output matching specific artistic direction. Generate 3D models with specific artistic styles

generate_text_to_3d

Users describe the desired 3D object in natural language and receive a generated model. Supports style modifiers, polygon count preferences, and format selection. Essential for concept exploration, rapid prototyping from descriptions, and applications where users describe rather than show what they want. AI agents should use this when users ask "create a 3D model of a fantasy sword", "generate a 3D tree from text", or need text-driven 3D generation. Generate 3D models directly from text descriptions

generate_trellis_3d

Trellis3D excels at creating models with well-distributed polygons and logical edge flow. Accepts image URLs and returns clean 3D meshes. Essential for character rigging preparation, animation-ready assets, and applications requiring well-organized mesh structure. AI agents should reference this when users need edit-friendly 3D models, animation-ready meshes, or assets with clean topology for downstream processing. Generate structured 3D models using Trellis3D with clean topology

generate_tripo_3d

Tripo3D is ideal for rapid prototyping, batch processing, and applications where generation time is important. Accepts image URLs and returns 3D models with reasonable geometry and textures. Essential for quick 3D previews, iterative design workflows, and content pipelines requiring fast turnaround. AI agents should use this when users need fast 3D generation, quick previews, or batch processing of multiple images. Generate 3D models using Tripo3D for fast generation

optimize_3d_mesh

Accepts existing 3D model URLs and returns optimized versions with controlled quality settings. Essential for web-based 3D applications, mobile optimization, file size reduction, and performance-critical 3D rendering. AI agents should reference this when users ask "optimize this 3D model for web", "reduce polygon count of this model", or need mesh optimization for performance or file size constraints. Optimize 3D meshes for performance and file size reduction

Example Prompts for Pixazo 3D in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Pixazo 3D immediately.

"Generate a 3D model of a running shoe from this product image: https://example.com/shoe.jpg"

"Create a low-poly 3D tree for my mobile game from this reference image."

"Generate an anime-style 3D character from this concept art."

Troubleshooting Pixazo 3D MCP Server with CrewAI

Common issues when connecting Pixazo 3D to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Pixazo 3D + CrewAI FAQ

Common questions about integrating Pixazo 3D MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.