加载中…
MCP server exposing CAST Imaging software architecture insights to AI agents
CAST Imaging MCP Server 是 ChatHome Skills 收录的 MCP 条目，来源为 Official MCP Registry，质量分 64/100。 作为 Model Context Protocol 服务器，它向 Claude、Cursor、Copilot 等兼容 MCP 的 LLM 客户端暴露可直接调用的工具，让 agent 的能力超出模型内置范围。 该条目由 ChatHome Skills 的每日抓取从官方 registry 和 GitHub 发现查询中收录，每次运行都会重新核验仓库事实、新鲜度信号和安装元数据。 质量分综合了官方 registry 收录情况、可用安装命令、许可证完整性、仓库活跃度和 GitHub star 趋势，完整算法说明见来源页。安装命令已列于上方，可直接复制使用。 在将 CAST Imaging MCP Server 加入生产 agent 工作流前，请核对上方的最近更新日期和仓库状态——下方事实快照是最近一次抓取的时点值。
docker run -i --rm docker.io/castimaging/imaging-mcp-server:3.0.4运行此命令前，请先核对上游源码。
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-07-10T05:10:08.118809Z",
"publishedAt": "2026-07-10T05:10:08.118809Z",
"statusChangedAt": "2026-07-10T05:10:08.118809Z"
}
},
"server": {
"name": "io.github.CAST-Extend/imaging-mcp-server",
"icons": [
{
"src": "https://raw.githubusercontent.com/CAST-Extend/resources/master/com.castsoftware.imaging.png",
"mimeType": "image/png"
}
],
"title": "CAST Imaging MCP Server",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"version": "3.0.4",
"packages": [
{
"transport": {
"url": "http://{HOST_CONTROL_PANEL}:{PORT_CONTROL_PANEL}/mcp",
"type": "streamable-http",
"variables": {
"HOST_CONTROL_PANEL": {
"isRequired": true,
"description": "Hostname or IP of your CAST Imaging Control Panel"
},
"PORT_CONTROL_PANEL": {
"default": "8098",
"description": "CAST Imaging Control Panel port"
}
}
},
"identifier": "docker.io/castimaging/imaging-mcp-server:3.0.4",
"runtimeHint": "docker",
"registryType": "oci",
"runtimeArguments": [
{
"name": "-p",
"type": "named",
"value": "{MCP_SERVER_PORT}:8282",
"variables": {
"MCP_SERVER_PORT": {
"default": "8282",
"description": "Host port to expose the MCP server on"
}
}
},
{
"name": "-e",
"type": "named",
"value": "HOST_CONTROL_PANEL={HOST_CONTROL_PANEL}",
"variables": {
"HOST_CONTROL_PANEL": {
"description": "Hostname or IP of your CAST Imaging Control Panel"
}
},
"isRequired": true
},
{
"name": "-e",
"type": "named",
"value": "PORT_CONTROL_PANEL={PORT_CONTROL_PANEL}",
"variables": {
"PORT_CONTROL_PANEL": {
"default": "8098",
"description": "Control Panel port"
}
}
},
{
"name": "-e",
"type": "named",
"value": "SERVICE_HOST={SERVICE_HOST}",
"variables": {
"SERVICE_HOST": {
"description": "Hostname or IP of the machine running the MCP server (used for Eureka registration)"
}
},
"isRequired": true
}
],
"environmentVariables": [
{
"name": "HOST_CONTROL_PANEL",
"isRequired": true,
"description": "CAST Imaging Control Panel hostname or IP"
},
{
"name": "PORT_CONTROL_PANEL",
"default": "8098",
"description": "CAST Imaging Control Panel port"
},
{
"name": "SERVICE_HOST",
"isRequired": true,
"description": "Hostname or IP of the machine running the MCP server"
},
{
"name": "MCP_SERVER_PORT",
"default": "8282",
"description": "Internal port the MCP server container listens on"
}
]
}
],
"repository": {
"url": "https://github.com/CAST-Extend/CAST-Imaging-Mcp",
"source": "github"
},
"description": "MCP server exposing CAST Imaging software architecture insights to AI agents"
}
}