Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Homelab log investigation over local logs: tail, errors, search, timeline, context.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"loglens": {
"command": "npx",
"args": [
"-y",
"@reneturcios/loglens",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add loglens -- npx -y @reneturcios/loglens mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"loglens": {
"command": "npx",
"args": [
"-y",
"@reneturcios/loglens",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"loglens": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/loglens",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 CloudCorpRecords 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.0)于4天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js, Docker。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
loglens investigates homelab logs held in a local file: what the store holds, what arrived most recently, what errored, what mentions a term, how volume is spread over time, and what surrounded a moment. One binary serves a command-line interface and a stdio MCP server exposing a single action-dispatched tool, cortex.
This is a labelled core subset. The tool it is modelled on dispatches 60 catalog actions; loglens implements seven of them — status, tail, errors, search, timeline, context, and help — and omits the other 53 (fleet and topology views, AI session analysis, correlation and anomaly analysis, error acknowledgement, notifications, and administration). The help action lists the implemented subset and the omitted actions at runtime.
Records live in a JSONL file: one JSON object per line, each with ts (an ISO-8601 timestamp), level, source, and message:
{"ts":"2026-10-26T09:15:00.000Z","level":"info","source":"docker/web","message":"container started"}
{"ts":"2026-10-26T09:16:12.000Z","level":"error","source":"syslog","message":"disk almost full"}
The path comes from --file on the CLI, then the LOGLENS_LOG_FILE environment variable, then ./loglens.jsonl. Malformed lines (bad JSON, missing fields, unparseable timestamps) are skipped and counted, never fatal. A missing file is a clean error for data actions; status instead reports the store state with exists: false, and help needs no store at all. All logic is local and deterministic — no network access, ever.
npx @reneturcios/loglens status
Or run the container image:
docker run -i ghcr.io/cloudcorprecords/loglens
The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead. Mount your log file and set LOGLENS_LOG_FILE to its in-container path.
export LOGLENS_LOG_FILE=/var/log/homelab.jsonl
loglens status loglens tail --limit 5 --source docker/web loglens errors --limit 10 loglens search "disk" --since 2026-10-26T00:00:00.000Z loglens timeline --bucket day loglens context 2026-10-26T09:16:12.000Z --window-minutes 5 loglens context 12 --limit 3 loglens help
loglens --version
Commands print a JSON result. tail, errors, and search return records newest first; context returns them in file order. context accepts either a timestamp (records within --window-minutes of it, or the --limit nearest records around the closest one) or a bare record index (the --limit records on either side of that position). Exit codes: 0 on success, 1 when an operation fails (including a missing log file), 2 for usage errors.
One bin serves both faces. The mcp subcommand starts a stdio MCP server:
npx -y @reneturcios/loglens mcp
MCP client configuration:
{
"mcpServers": { "loglens": { "command": "npx", "args": ["-y", "@reneturcios/loglens", "mcp"], "env": { "LOGLENS_LOG_FILE": "/absolute/path/to/logs.jsonl" } } } }
| Tool | Input | What it returns |
|---|---|---|
cortex | action (required, one of status, tail, errors, search, timeline, context, help), plus optional query, source, level, limit, since, until, bucket (hour or day), timestamp, window_minutes | Per action: a store summary, the latest matching records, hourly/daily volume buckets, records around a moment, or the subset help text. |
A useful first call is {"action":"status"}, then narrow with tail, errors, search, timeline, or context.
npm install
npm run build # tsc -> dist/ npm test # node test runner over test/*.test.ts, real temp JSONL files, no network npm run dev # run the CLI from source via tsx
MIT — see LICENSE.