MCP server that enables AI Agents to use images and events from Safie camera devices
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"Safie API": {
"env": {
"ACCESS_TOKEN": "******"
},
"args": [
"run",
"--with",
"git+https://git@github.com/SafiePublic/safie-api-mcp-server.git",
"safie-api-mcp-server"
],
"command": "uv"
}
}
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Safie APIを利用してデバイスの情報取得や操作を行うためのMCP (Model Context Protocol) サーバ
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Safie APIを利用してデバイスの情報取得や操作を行うためのMCP (Model Context Protocol) サーバ
[!NOTE] 本実装はプレビュー版であり一部の機能のみを試験的に提供しています。 サポート対象外となりますのでご了承の上、お使いください。
以下の環境変数のどちらかが設定されている必要があります
ACCESS_TOKEN: Safie Developers OAuth2認証アプリケーションで発行したOAuth2アクセストークンAPI_KEY: Safie Developers APIキー認証アプリケーションで発行したAPIキー両方指定した場合、ACCESS_TOKEN が利用されます
Python 3.10+, uvが手元にインストールされている場合は以下の設定を追加することで利用できます
{
"mcpServers": {
"Safie API": {
"command": "uv",
"args": [
"run",
"--with",
"git+https://git@github.com/SafiePublic/safie-api-mcp-server.git",
"safie-api-mcp-server"
],
"env": {
"ACCESS_TOKEN": "******"
}
}
}
}
Dockerを用いて利用する場合は、まず以下のようにイメージをビルドします
$ docker build -t safie-api-mcp-server .
その後、以下の設定を追加することで利用できます
{
"mcpServers": {
"Safie API": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"ACCESS_TOKEN",
"-e",
"API_KEY",
"safie-api-mcp-server"
],
"env": {
"ACCESS_TOKEN": "******"
}
}
}
}