F
licenseNot graded
qualityC
maintenanceProvides multi-model AI image generation via MCP tools, supporting Seedream, SDXL, and FLUX models with GPU acceleration.
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Segmind MCP Server
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TDQS
A3.7/5.0
Scored across 12 tools
Disambiguation4/5
Most tools are clearly separated by modality and action: generate_image, transform_image, enhance_image, generate_video, generate_audio, and generate_music all have distinct purposes. The only real overlap is prepare_image versus read_local_image, though the descriptions explicitly differentiate the recommended workflow from the base64-returning alternative.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern: generate_*, list_*, get_*, transform_*, enhance_*, estimate_*, check_*, prepare_*, and read_*. The verbs are descriptive and predictable across the entire set.
Tool Count5/5
Twelve tools is well-scoped for a multimodal generation server. The count covers image, video, audio, and music generation, model discovery, image utilities, cost estimation, and credit checking without unnecessary bloat.
Completeness5/5
The tool surface provides a complete workflow for the domain: model discovery, generation across multiple modalities, image transformation and enhancement, local image preparation, and account/cost management. There are no obvious dead ends or missing core operations for the stated purpose.
Maintenance
ActivityInactive
ResponsivenessNo issues