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MCP Vision Adapter

@MetehanYasar11

代码仓库

基本信息

分类

开发工具

许可证

MIT license

传输方式

stdio

作者

MetehanYasar11

关于 MCP Vision Adapter

暂无概览

MCP Vision Adapter 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

MCP Vision Adapter 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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.

常见问题

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`.

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