What transport does mttrly use?
mttrly uses remote Streamable HTTP; it does not expose a local stdio surface.
@mttrly-hq
基本信息
Remote Streamable HTTP MCP server for AI SRE workflows: server health, alerts, diagnostics, playbooks, approvals, audit history, deploy verification, and safe server inspection. Uses OAuth 2.1 with PKCE.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mttrly": {
"url": "https://api.mttrly.com/mcp"
}
}
}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。
点击上方按钮,直接连接服务器端点实时获取工具列表。
mttrly is a remote Streamable HTTP MCP connector that provides AI-powered incident management and server monitoring. It integrates with the mttrly Central API to access an AI SRE agent for server health, diagnostics, playbooks, approvals, and audit history. It is designed for users who need to monitor and manage remote servers through MCP-compatible clients.
Connect via the mttrly connector UI in Claude.ai or Claude Desktop by adding a custom connector with URL https://api.mttrly.com/mcp and completing OAuth. For Claude Code, run claude mcp add --transport http mttrly https://api.mttrly.com/mcp. For OpenAI Codex, add the URL to ~/.codex/config.toml and run codex mcp login mttrly. Cursor users can add the same URL as a remote MCP server. Always call mttrly_get_capabilities first to discover available tools and plan restrictions.
mttrly uses remote Streamable HTTP; it does not expose a local stdio surface.
Authentication uses OAuth 2.1 with PKCE S256 against `https://app.mttrly.com`. Browser-origin clients must be allowlisted.
Two plans exist: Watchdog (read‑only tools, e.g., server status, alerts) and Deployment Bro (full read/execute tools, including diagnostics and playbooks).
No. Always call `mttrly_get_capabilities` first to see available tools, restricted tools, and plan limits.
Actions such as playbook execution or shell commands return `pending_approval`. Pending actions expire after 30 minutes; use `mttrly_approve_action` or `mttrly_cancel_action` after explicit user confirmation.
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