Static source inference · medium confidence · detected: Logging
Deprecated protocol patterns detected
Summary
This server has 4 tools with basic but incomplete definitions. All tools have short, clear descriptions (good) and proper input schemas with typed parameters (good), but lack critical details required for production use. Parameter descriptions are minimal or absent, output schemas are completely undocumented, error handling lacks recovery guidance, and there are no security annotations. The naming is verb-forward (good), but the schema documentation and parameter clarity fall short of A/B standards. This is typical C-grade community work.
Tools (4)
edit_imagewriteauthsource verified63/100
Edit an image using the Gemini Flash Edit model.
generate_imagewriteauthsource verified63/100
Generate an image using the Flux model.
generate_image_lorawriteauthsource verified67/100
Generate an image using the Flux model with a LoRA.
generate_videowriteauthsource verified65/100
Generate a video based on a prompt and an initial image using the wan-i2v/turbo model.
Output schemas completely undocumented. Tools return file paths as strings (e.g., 'The image or video was successfully generated and saved at: /path/to/file'). LLMs cannot plan downstream operations without knowing what fields and types are returned.
Parameter 'prompt' lacks description in all 4 tools. The parameter 'image_path' in edit_image and generate_video lacks description. The parameter 'negative_prompt' in generate_video is described only generically ('Text describing what should not appear').
Tool descriptions are under 100 characters and lack context for when/why to use them. 'Generate an image using the Flux model' does not explain when to choose this over generate_image_lora, what the constraints are (e.g., image size always 512x512), or what happens on failure.
Recommendations
Document output schemas for all 4 tools. Example for generate_image: '{"type": "object", "properties": {"filepath": {"type": "string", "description": "Absolute path to saved PNG file"}, "url": {"type": "string", "description": "Fal AI image URL"}, "width": {"type": "integer"}, "height": {"type": "integer"}}, "required": ["filepath"]}'
Add descriptions to all parameters. Example: 'prompt' → 'The text prompt for image generation (1-1000 characters; plain text, no markdown)'. 'image_path' → 'Absolute or relative file path to the input image (supports PNG, JPEG, WebP; max 10 MB)'. 'lora_scale' → 'Strength of the LoRA effect (0.0 - 2.0; default 1.0 for no modification)'.
Expand tool descriptions to 100 - 200 characters. Example for generate_image: 'Generate a high-quality 512×512 PNG image from a text prompt using the Flux dev model. Returns local file path and image dimensions. Safe to retry with same prompt. Use generate_image_lora for custom style fine-tuning.'
Add error handling with recovery guidance. Example: 'if not os.environ.get("SAVE_MEDIA_DIR"): return {"error": "SAVE_MEDIA_DIR not configured. Ask the agent operator to set this environment variable.", "retryable": false}'. For API failures: 'return {"error": f"Image generation failed: {e.message}. Retry in 30s or check Fal AI service status.", "retryable": true}'
Validate image_path against path traversal. Use os.path.abspath() and assert it starts with an allowed base directory. Example: 'import os; real_path = os.path.abspath(image_path); if not real_path.startswith(ALLOWED_DIR): raise ValueError(f"Access denied: {real_path} outside {ALLOWED_DIR}")'
Spec posture evidence
Inferred effective spec: <=2025-11-25.
Relies on Logging (deprecated) - log to stderr or use OpenTelemetry
No error handling or recovery guidance. Code raises bare Exception() (e.g., 'Error generating or saving the image or video', 'SAVE_MEDIA_DIR environment variable not set'). LLMs receive these errors with no actionable next steps.
No permission checks or scope declarations. Tools write files to SAVE_MEDIA_DIR and upload files to Fal AI without any authentication validation or audit logging.
No tool annotations for destructiveness, read-only status, or idempotence. These are WRITE tools (per Risk field) but lack destructiveHint annotations that would help agents plan safely. Per spec: tool annotations (readOnlyHint/destructiveHint/idempotentHint) are current patterns.
No pagination or result limits. Tools return single file paths, which is fine, but generate_video and generate_image_lora accept arbitrary scale/step/frame parameters with no documented constraints.
Potential path traversal vulnerability. edit_image and generate_video accept 'image_path' as a string parameter with no validation. A malicious agent could pass '../../../etc/passwd' or absolute paths.
edit_imagegenerate_video
Add per-parameter min/max constraints. For numeric params (lora_scale, num_inference_steps, num_frames, resolution), include in the schema and description. Example: '"lora_scale": {"type": "number", "minimum": 0.0, "maximum": 2.0, "default": 1.0}'
Add permission/scope checks. Example: '@requires_permission("write:fal-ai") async def generate_image(...)' or check an agent role/token before executing. Log the caller and operation.
Annotate tools with destructiveHint=true in the FastMCP registration to signal to agents that these are write operations. Example: '@mcp.tool(description="...", hints={"destructiveHint": true})'
Improve parameter naming for clarity. Change 'image_path' to 'image_file_path' or 'local_image_path' to distinguish from 'image_url'. This prevents agents from confusing local and remote image references.
Add timeout parameters or document default timeouts. Fal AI requests can hang; set explicit limits (e.g., 5 min timeout). Return timeout errors with retry guidance.