ModelScope MCP Server
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Alternatives to ModelScope MCP Server
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Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables text-to-image and image-to-image generation through the ModelScope API-Inference, including LoRA model support and local image input. It also provides keyword-based ModelScope model search for finding diffusion models and LoRA libraries.MIT
- FlicenseCqualityDmaintenanceEnables AI assistants to manage Alibaba Cloud resources via natural language, with explicit tools for common services and a universal API invoker for full cloud coverage.92-

Meshy MCP Serverofficial
AlicenseNot gradedqualityCmaintenanceEnables AI agents to create, manage, and download 3D models, textures, images, rigged characters, and animations through natural conversation.1,578 npm46MIT- AlicenseNot gradedqualityFmaintenanceEnables AI assistants to operate Huawei Cloud resources (ECS, OBS, GaussDB, etc.) through conversational workflows via the Model Context Protocol.Apache 2.0
- FlicenseNot gradedqualityDmaintenanceEnables AI agents to browse, search, and purchase 74+ AI products and services across 7 categories, with free demos and Alipay payment integration.-
- AlicenseBqualityDmaintenanceEnables text-only models to process images and other media formats by providing access to multimodal models from OpenAI and Dashscope (Alibaba Cloud). Supports flexible deployment options and comprehensive tooling for multimodal AI interactions.34MIT
TDQS
Scored across 9 tools
Each tool targets a distinct resource: user, environment, models, datasets, studios, papers, MCP servers, and image generation. There is no overlap between search actions, and get_mcp_server_detail is clearly a follow-up to search_mcp_servers.
All tools follow a consistent verb_noun pattern with lowercase snake_case: get_*, search_*, and generate_image. No mixed conventions or vague verbs.
With 9 tools, the server is well-scoped. The count covers user info, environment info, search across five content types, a detail fetch for MCP servers, and image generation—each earning its place.
The search tools cover discovery for models, datasets, studios, and papers, but only MCP servers have a dedicated detail endpoint. This creates a notable gap: after searching for a model or dataset, there is no way to fetch full details, which could hinder workflows that require specific resource metadata.