mcp-server-cvdlt

MRonaldo-gif/mcp-server-cvdlt

3.3
research_and_dataai_chatbot

If you are the rightful owner of mcp-server-cvdlt and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

Python server implementing Model Context Protocol (MCP) for image object detection, segmentation, and pose estimation operations.

Tools

Functions exposed to the LLM to take actions

detect_objects

Detect objects in an image using YOLOv10. Returns JSON array of detected objects with bounding boxes, confidence scores, and class labels.

segment_objects

Segment objects in an image using YOLOv8. Returns JSON array of segmented objects with bounding boxes, confidence scores, and class labels.

segment_image

Segment entire image using Ultralytics SAM. Returns JSON array of segmented regions with bounding boxes, areas, and confidence scores.

estimate_pose

Estimate human poses in an image using YOLOv8. Returns JSON array of detected poses with keypoint coordinates and confidence scores.

Prompts

Interactive templates invoked by user choice

No prompts

Resources

Contextual data attached and managed by the client

No resources

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