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MCP Vision Adapter

@MetehanYasar11

リポジトリ

基本情報

カテゴリ

開発者ツール

ライセンス

MIT license

トランスポート

stdio

作者

MetehanYasar11

MCP Vision Adapter について

概要はまだありません

MCP Vision Adapter の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-vision-adapter": {
      "command": "python",
      "args": [
        "-m",
        "mcp_vision_adapter.main"
      ]
    }
  }
}

MCP Vision Adapter のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Vision Adapter?

MCP Vision Adapter is a universal, open-source MCP (Model Context Protocol) adapter for all CLI projects. It modernizes and connects classic automations, scripts, and detection tools to LLM/agent ecosystems.

How to use MCP Vision Adapter?

Run the YOLOv8 service and the adapter using Docker Compose, or set up a virtual environment, install dependencies, and start both services with Uvicorn. Invoke via HTTP/STDIO or VS Code Copilot Agent mode using endpoints like /execute with tool detect_objects and input parameters.

Key features of MCP Vision Adapter

  • Ultralytics YOLOv8 integration for object detection, segmentation, and pose estimation.
  • REST & STDIO API for flexible integration.
  • Web UI for model management via Streamlit.
  • VS Code Copilot Agent mode support.
  • Easy Docker Compose setup.
  • Video and image analysis capabilities.

Use cases of MCP Vision Adapter

  • Turn legacy CLI automations into LLM/agent tools without rewriting code.
  • Perform object detection on images and videos directly from agent workflows.
  • Hot‑swap detection models on a running service.
  • Connect any CLI‑based tool as an agent tool via the MCP protocol.

よくある質問

1

What is the MCP protocol version used?

MCP Protocol Version `2024-03-26`.

2

How can I run the project without Docker?

Create a Python virtual environment, install dependencies from `yolov8_service/requirements.txt`, then start the YOLOv8 service on port 8080 and the adapter on port 3000.

3

Does MCP Vision Adapter support VS Code Copilot via STDIO?

VS Code Copilot tool execution via STDIO is currently not supported. Use the HTTP API for full integration; this will be fixed in an upcoming update.

4

What if port 3000 is already in use?

Stop the previous process (CTRL‑C) or run the adapter with `--port 3001` and update `mcp.json` accordingly.

5

Where are the custom models stored and how to mount them?

Default weights file is `/weights/yolov8n.pt`. Mount your model folder with `docker run -v ${PWD}/models:/weights`.

コメント

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