A
licenseNot graded
qualityC
maintenanceEnables external AI agents to programmatically inspect, edit, and export image documents through tools for layers, selections, painting, adjustments, masks, history, and compositing.
MIT
Firefly MCP Server
by thenavidm
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TDQS
B3.4/5.0
Scored across 14 tools
Disambiguation4/5
Most tools target distinct operations: generate_image, generate_similar, generate_video, generative_expand, generative_fill, upscale_image, and the utility tools (upload_image, get_job_status, list_custom_models, verify_credentials) are clearly separable. The three compositing tools (generate_object_composite, precise_composite, adaptive_composite) have terse, near-parallel descriptions that give an agent little basis for choosing among them, though they are genuinely different operations.
Naming Consistency3/5
All names use snake_case, which is good, but verb/prefix conventions are mixed: 'generate_', 'generative_', 'precise_', 'adaptive_', 'upscale_', plus utility verbs 'get_', 'list_', 'upload_', 'verify_'. The composite tools omit a verb entirely, and 'generate_image5' uses an unexplained numeric suffix that breaks the pattern.
Tool Count5/5
Fourteen tools is well-scoped for a media-generation API surface, with each tool mapping to a distinct Firefly capability (generation, editing, compositing, video, upscaling, upload, job polling, models, auth). No obvious redundancy or padding.
Completeness4/5
The set covers the full generation/edit lifecycle plus async job polling, uploads, model listing, and credential verification. Minor gaps exist: no explicit job cancel/delete or asset download/retrieval tool, and no batch or clear error-recovery path beyond get_job_status, but core workflows are covered.
Maintenance
ActivityNo data
ResponsivenessSyncing