Deploy an MCP Server on Raspberry Pi 5 for AI agent interaction using OpenAI SDK
Learn how to deploy a Model Context Protocol server on Raspberry Pi 5 and use the OpenAI Agent SDK to create AI agents with custom tools for local inference.
Evaluation Conditions
Keypoint Detection · Raspberry Pi 5 · INT8 · 640×640 · coco_pose
| Metric | Resultsvs baseline | Change | |
|---|---|---|---|
| End to end latency p50 | 234.00ms335.84ms | −101.84 ms | |
| End to end latency p90 | 234.18ms336.10ms | −101.92 ms | |
| End to end latency p99 | 234.35ms337.39ms | −103.04 ms | |
| Peak memory | 59.19MB75.39MB | −16.20 MB | |
| Average memory | 58.00MB74.47MB | −16.47 MB | |
| Time to first inference | 246.90ms376.58ms | −129.68 ms | |
| Frames per second | 4.27fps2.98fps | +1.29 fps | |
| mAP@0.50:0.95 | 46.38%47.37% | −0.99% | |
| mAP@0.50 | 75.79%75.95% | −0.16% | |
| mAP@0.75 | 49.62%50.68% | −1.06% |
The Optimized Model is provided as a reference implementation to demonstrate and evaluate execution and performance on Arm-based systems. It is not a production-ready or supported solution.
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| Configuration | Baseline | Arm Optimized |
|---|
| Dataset | coco_pose | coco_pose |
| Sample count | 5,000 | 5,000 |
| Batch size | 1 | 1 |
| Input resolution | 640x640 | 640x640 |
| Runs | 100 | 100 |
| Warmup runs | 10 | 10 |