OpsLevel MCP
OfficialOpsLevel MCP 服务器
该 MCP(模型上下文协议)服务器为 AI 提供了与您的 OpsLevel 帐户交互的工具。
特征
目前,MCP 服务器仅使用对您的 OpsLevel 帐户的只读访问权限,并且可以从以下资源读取数据:
行动
成分
文档(API 和技术文档)
域
过滤器
基础设施
存储库
系统
团队
用户
设置
安装 MCP 服务器
Homebrew -
brew install opslevel/tap/opslevel-mcpDocker-
docker pull public.ecr.aws/opslevel/mcp:latest
您还可以使用固定版本查看图库中可用的标签手册 - 访问我们的GitHub 发布页面并下载适合您的操作系统的二进制文件。
您将需要一个API 令牌来授权 MCP 服务器通过环境变量与您的帐户对话。
为您选择的 AI 工具设置 MCP 配置。
克劳德
根据 Claude Desktop 文档编辑指定路径下的文件
Mac OS -
${HOME}/Library/Application\ Support/Claude/claude_desktop_config.jsonWindows——
%APPDATA%\Claude\claude_desktop_config.json
启动(或重启)Claude Desktop
{
"mcpServers": {
"opslevel": {
"command": "opslevel-mcp",
"env": {
"OPSLEVEL_API_TOKEN": "XXXXXXX"
}
}
}
}Related MCP server: devops-mcp-server
VS 代码
打开“设置”菜单(Command + 逗号),然后在页面顶部选择适合您用例的正确选项卡
工作区 - 在工作区环境中配置服务器
用户 - 在您的用户上下文中配置服务器
选择功能 → 聊天
确保“Mcp”已启用
您可能需要让您的 Github 管理员在组织的 CoPilot 设置中启用“预览”功能。
点击“Mcp > Discovery”下的“Edit in settings.json”获取以下配置
也可以直接编辑文件
(Mac OS)
${HOME}/Library/Application\\ Support/Code/User/settings.json
启动(或重启)VS Code
{
"chat.agent.enabled": true,
"chat.mcp.discovery.enabled": true,
"mcp": {
"inputs": [
{
"type": "promptString",
"id": "opslevel_token",
"description": "OpsLevel API Token",
"password": true
}
],
"servers": {
"opslevel": {
"type": "stdio",
"command": "opslevel-mcp",
"env": {
"OPSLEVEL_API_TOKEN": "${input:opslevel_token}"
}
}
}
}
}光标
打开光标菜单并选择设置 → 光标设置 → MCP
点击“添加新的全局 MCP 服务器”
添加以下配置
{
"mcpServers": {
"opslevel": {
"command": "opslevel-mcp",
"env": {
"OPSLEVEL_API_TOKEN": "XXXXXX"
}
}
}
}风帆冲浪
导航至“Windsurf”-“设置”>“高级设置”
向下滚动到 Cascade 部分,您将找到添加新服务器的选项
使用以下配置编辑mpc_config.json
重启风帆冲浪
{
"mcpServers": {
"opslevel": {
"command": "opslevel-mcp",
"env": {
"OPSLEVEL_API_TOKEN": "XXXXXX"
}
}
}
}Docker
如果你没有直接安装二进制文件,而是拉取 Docker 镜像,则需要调整上述 MCP 配置以支持通过 Docker 运行服务器
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"OPSLEVEL_API_TOKEN",
"public.ecr.aws/opslevel/mcp:latest"
],This server cannot be installed
Maintenance
Resources
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If you are the server author, to access and configure the admin panel.
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/OpsLevel/opslevel-mcp'
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