A
licenseNot graded
qualityD
maintenanceEnables interaction with fal.ai AI models through MCP, supporting model discovery, content generation, queue management, and file uploads to the fal.ai platform.
MIT
fal
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TDQS
A4.8/5.0
Scored across 8 tools
Disambiguation5/5
Each tool has a distinct, non-overlapping purpose: cancelling requests, checking status, encoding files, fetching schemas, retrieving results, listing models, running synchronously, and submitting asynchronously. No confusion possible.
Naming Consistency5/5
All tools follow a consistent fal_verb_noun pattern (e.g., fal_cancel_request, fal_get_result, fal_list_models). Even compound verbs like encode_file_as_data_uri maintain the structure.
Tool Count5/5
8 tools is ideal for this scope: covering discovery, synchronous and asynchronous execution, result handling, and a utility. Neither too few nor too many.
Completeness5/5
The set covers the full lifecycle: model discovery (list_models, get_model_schema), execution (run_model, submit_request), status tracking (check_status), result retrieval (get_result), cancellation (cancel_request), and a local file encoding helper. No obvious gaps.
Maintenance
ActivitySlowing
ResponsivenessNo issues