"3D content, models, or technology" matching MCP servers:

An MCP server for managing and publishing 3D files using S3-compatible storage providers like Cloudflare R2 and AWS S3. It enables users to upload models, generate interactive 3D viewers, and manage temporary access via presigned URLs.

Enables managing SAP Cloud Integration iFlows, packages, configurations, deployments, and runtime artifacts via natural language through the OData API.

Uploads files, text, or base64 binary content to Aliyun OSS as objects with MD5-based keys, returning status, size, key, and URL.

The Hostinger MCP server enables seamless integration of Hostinger’s API with AI tools. This server exposes Hostinger API endpoints as callable tools, allowing AI models to fetch live data or perform real-time actions on hosting infrastructure.

Enables AI agents to search Vast.ai GPU marketplace, deploy compute-heavy video models or ComfyUI, and guarantee instances are torn down after the job finishes.

Enables generating 3D models, slicing them with Polar Cloud defaults, and queuing prints from MCP clients.

Enables AI agents to discover models, pricing, and chat completions through RouterBase, an API gateway for 200+ AI models.

Enables AI models to interact with Akave's S3-compatible storage by providing tools for managing storage buckets and objects through standardized Model Context Protocol (MCP).

Enables large language models to automatically report customer-facing issues with Azure resources by parsing natural language requests and submitting impact reports through the Azure Management API.

MCP server enabling AI models to list S3 buckets, objects, and download files securely.

A service that enables rapid deployment of HTML content to EdgeOne Pages and automatically generates publicly accessible URLs for the deployed content.

Run, build, train, and deploy ML models on the cloud.

An implementation of the Model Context Protocol server that enables AI models to communicate with Edge Security Acceleration (ESA) services, allowing models to manage routines, deployments, routes, records, and sites through standardized protocols.

A Python MCP server that lets you manage Microsoft Fabric through natural language in Claude Code or Claude Desktop, with 77+ tools covering workspaces, lakehouses, warehouses, SQL, DAX, semantic models, notebooks, pipelines, OneLake, and Microsoft Graph.

Enables AI assistants to deploy and manage hosted apps from git repos, read logs, add Postgres databases and domains, manage API keys and budgets, and send requests to 200+ AI models. Connects over remote Streamable HTTP with OAuth sign-in, so users need no API keys, installs, or local server.

Connects Claude and other MCP-compatible AI assistants to a Coreflux MQTT broker, enabling them to discover and execute Coreflux commands for managing models, actions, rules, and routes through natural language.

Enables secure access to Xplainable AI platform capabilities for managing machine learning models, deployments, and preprocessors. Supports both read operations (listing models, deployments) and write operations (deploying models, generating reports) with proper authentication and rate limiting.

Enables AI assistants to fetch live, dated prices for LLM models and cloud compute instances across providers, compare and recommend models, and estimate monthly costs based on workload-specific token shapes and constraints.

Enables large language models to directly access Tencent Cloud Log Service for log search, metric queries, and alarm management without code.

Enables LLMs to interact with Cloudera AI Workbench APIs for managing files, jobs, models, experiments, projects, and applications.