Add Copilot instructions and MCP configuration files

.github/copilot-instructions.md

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+# AI Coding Agent Instructions
+
+## Project Overview
+This is an OpenPose-based image generation server that integrates with ComfyUI for AI image generation. The system processes pose coordinates to generate skeleton images and sends them to ComfyUI for final image generation.
+
+## Architecture & Key Components
+
+### Core Service Flow
+1. **Flask API** (`app.py`) receives pose coordinates via REST endpoints
+2. **OpenPose Generation** (`openpose_gen.py`) converts coordinates to skeleton images
+3. **ComfyUI Integration** uploads images and queues generation workflows
+4. **Skeleton Library** (`skeleton_lib.py`) handles pose drawing with different formats (COCO, Body25)
+
+### Critical Dependencies
+- **ComfyUI Server**: External service at `localhost:8188` for AI image generation
+- **OpenCV**: For image processing and skeleton rendering
+- **Flask**: REST API server
+- **requests-toolbelt**: For multipart file uploads to ComfyUI
+
+## Development Patterns
+
+### Coordinate System Convention
+- Input coordinates are flat arrays: `[x1, y1, confidence1, x2, y2, confidence2, ...]`
+- Use `coordinates_to_keypoints()` to convert to `Keypoint` objects
+- Support both single pose (`/gen_image`) and multi-pose (`/gen_group_pic`) workflows
+
+### File Naming & Counters
+- Output images use incremental counters: `body_pose_output0000.png`, `body_pose_output0001.png`
+- Each function maintains its own static counter using `hasattr()` pattern
+- Circular queue naming for ComfyUI uploads with hash-based names
+
+### MCP Integration
+- Use `context7` defined in `.vscode/mcp.json` for coding tasks
+- Use `python-language-server` MCP for Python coding assistance
+- Use `analyzer` MCP for code analysis tasks
+
+### ComfyUI Workflow Integration
+- Workflow templates stored as JSON: `fencerAPI.json`, `group_pic.json`
+- Modify seed values for randomization: `prompt["3"]["inputs"]["seed"] = random.randint(0, 10000000000)`
+- Reference uploaded images by name in workflow nodes: `prompt["17"]["inputs"]['image'] = openpose_image_name`
+
+### Error Handling Pattern
+```python
+if not coordinates or not canvas_size:
+    return jsonify({"status": "error", "message": "Missing data"}), 422
+```
+
+## Key Functions to Understand
+
+### `save_bodypose()` / `save_bodypose_mulit()`
+- Converts coordinates to skeleton images using CV2
+- Creates output directory if missing
+- Returns image path for ComfyUI upload
+
+### `upload_image_circular_queue()`
+- Manages unique image names per user/session using SHA256 hash
+- Implements circular queue to prevent infinite file accumulation
+- Essential for ComfyUI integration
+
+### `queue_prompt()`
+- Sends workflow JSON to ComfyUI `/prompt` endpoint
+- Triggers actual AI image generation
+
+## Development Workflow
+
+### Testing API Endpoints
+```bash
+# Single pose generation
+curl -X POST -H "Content-Type: application/json" \
+  -d '{"coordinates": [x1,y1,conf1,...], "canvas_size": [width,height], "pid": "user123"}' \
+  http://localhost:5000/gen_image
+```
+
+### Running the Server
+```bash
+python app.py  # Starts Flask in debug mode on localhost:5000
+```
+
+### Skeleton Format Support
+- **COCO format**: 18 keypoints (default for single poses)
+- **Body25 format**: 25 keypoints (used in `main()` function)
+- Use corresponding `limbSeq` and `colors` arrays from `skeleton_lib.py`
+
+## Integration Points
+
+### ComfyUI Server Requirements
+- Must be running on `localhost:8188`
+- Requires `/upload/image` and `/prompt` endpoints
+- Workflow JSON files must match ComfyUI node structure
+
+### Output Directory Structure
+```
+output/                    # Generated skeleton images
+embeddings/               # ComfyUI embeddings and models
+script_examples/          # API usage examples
+```
+
+## Common Modifications
+
+## Adding New API Endpoints
+1. Define new Flask route in `app.py`
+2. Create corresponding handler function
+3. Follow existing patterns for input validation, image generation, and ComfyUI queuing
+
+### Adding New Pose Formats
+1. Define new `limbSeq` and `colors` in `skeleton_lib.py`
+2. Update coordinate conversion in `coordinates_to_keypoints()`
+3. Modify canvas drawing in `save_bodypose()`
+
+### New ComfyUI Workflows
+1. Export workflow from ComfyUI as JSON
+2. Save in project root (e.g., `new_workflow.json`)
+3. Create API function following `gen_fencer_prompt()` pattern
+4. Add Flask endpoint in `app.py`
+
+### Debugging ComfyUI Integration
+- Check ComfyUI server status at `http://localhost:8188`
+- Verify uploaded images in ComfyUI interface
+- Monitor workflow queue for errors
+- Use `script_examples/` for isolated testing

.vscode/mcp.json

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+{
+    "servers": {
+        "github-mcp": {
+            "type": "http",
+            "url": "https://api.githubcopilot.com/mcp"
+        },
+        "python-language-server": {
+            "command": "mcp-language-server",
+            "args": [
+                "--workspace",
+                "${workspaceFolder}",
+                "--lsp",
+                "pylsp"
+            ],
+        },
+        "analyzer": {
+            "command": "uvx",
+            "args": ["mcp-server-analyzer"]
+        },
+        "context7": {
+            "type": "stdio",
+            "command": "npx",
+            "args": ["-y", "@upstash/context7-mcp"]
+        }
+    }
+}