Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Syslog receiver and MCP server for homelab log intelligence.
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。
CORTEX_RECEIVER_HOST, CORTEX_TOKEN, CORTEX_RECEIVER_PORT标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
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 …”。
适用于网页版、桌面版和手机版 Claude:
https://cortex.tootie.tv/mcp打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"cortex": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CORTEX_RECEIVER_HOST",
"-e",
"CORTEX_TOKEN",
"-e",
"CORTEX_RECEIVER_PORT",
"ghcr.io/jmagar/cortex:v3.9.0"
],
"env": {
"CORTEX_RECEIVER_HOST": "your-value",
"CORTEX_TOKEN": "your-value",
"CORTEX_RECEIVER_PORT": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add --transport http cortex https://cortex.tootie.tv/mcpclaude mcp add cortex --env CORTEX_RECEIVER_HOST=your-value --env CORTEX_TOKEN=your-value --env CORTEX_RECEIVER_PORT=your-value -- docker run -i --rm -e CORTEX_RECEIVER_HOST -e CORTEX_TOKEN -e CORTEX_RECEIVER_PORT ghcr.io/jmagar/cortex:v3.9.0运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"cortex": {
"url": "https://cortex.tootie.tv/mcp"
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"cortex": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CORTEX_RECEIVER_HOST",
"-e",
"CORTEX_TOKEN",
"-e",
"CORTEX_RECEIVER_PORT",
"ghcr.io/jmagar/cortex:v3.9.0"
],
"env": {
"CORTEX_RECEIVER_HOST": "your-value",
"CORTEX_TOKEN": "your-value",
"CORTEX_RECEIVER_PORT": "your-value"
}
}
}
}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": {
"cortex": {
"type": "http",
"url": "https://cortex.tootie.tv/mcp"
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"cortex": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CORTEX_RECEIVER_HOST",
"-e",
"CORTEX_TOKEN",
"-e",
"CORTEX_RECEIVER_PORT",
"ghcr.io/jmagar/cortex:v3.9.0"
],
"env": {
"CORTEX_RECEIVER_HOST": "your-value",
"CORTEX_TOKEN": "your-value",
"CORTEX_RECEIVER_PORT": "your-value"
}
}
}
}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。
ChatGPT 只能连接互联网上的服务器:
https://cortex.tootie.tv/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
CORTEX_RECEIVER_PORT env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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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7日
发布者(tootie.tv)不是仓库所有者(jmagar);可能是其他人代为上架的
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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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 0 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。
你需要填写:CORTEX_RECEIVER_HOST, CORTEX_TOKEN
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于–,最新版本(3.9.0)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, FlyDocs
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.
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。
Self-hosted homelab log intelligence over MCP, CLI, and REST with SQLite/FTS.
It collects logs and operational evidence, stores them in SQLite with FTS5 search, and exposes one shared intelligence layer through CLI, REST, MCP, and a bundled browser workspace.
Cortex began as a syslog receiver. It now covers network logs, Docker, managed files, OpenTelemetry logs, metrics, and traces, host heartbeats, fleet inventory, shell and agent activity, and Claude, Codex, Gemini CLI, and Antigravity transcripts. It correlates those sources into timelines, incidents, and an evidence-backed topology graph without making the graph a second source of truth.
| Area | What Cortex provides |
|---|---|
| Ingest | UDP/TCP syslog, OTLP/HTTP logs, metrics, and traces, Docker logs and events, managed file tails, host heartbeats, AI transcripts, shell history, agent command records, and fleet inventory |
| Storage | SQLite in WAL mode, FTS5 full-text search, bounded metadata, retention, storage budgets, maintenance jobs, checkpoints, and 63 sequential schema migrations |
| Investigation | Search, filtering, context, timelines, patterns, anomaly comparison, cross-source correlation, recurring error signatures, deterministic incident bundles, and graph explanations |
| Fleet intelligence | SSH and API inventory collectors, host state, service topology, container and route relationships, redacted evidence, and rebuildable graph projections |
| AI operations | Claude, Codex, Gemini CLI, and Antigravity session indexing; skill, MCP, and hook event extraction where each provider exposes them; incident clustering; and guarded local LLM assessments |
| Interfaces | Native CLI, one action-dispatched MCP tool, authenticated REST APIs, MCP prompts and resources, an MCP Apps search widget, and a bundled investigation workspace |
| Operations | Setup and repair, diagnostics, Compose control, backup, integrity checks, WAL checkpoints, vacuum, update workflows, agents, and health endpoints |
[!IMPORTANT]
Cortex is designed for a trusted homelab or small private fleet. It is not a clustered log warehouse, a general-purpose SIEM, or a safe place to expose unauthenticated administrative surfaces to the public internet.
The first-class guided path is:
npx skills add dinglebear-ai/cortex --skill install-cortex
Start a fresh agent task and invoke $install-cortex. It chooses server or client-only role, delegates to the canonical installer/setup engine, configures auth/network/storage, and verifies the live client connection.
The npm launcher remains the fastest manual path for local CLI and stdio MCP use:
npx -y @dinglebear/cortex --help
npx -y @dinglebear/cortex mcp
Install it permanently with:
npm install --global @dinglebear/cortex
cortex --version
The launcher requires Node.js 18 or newer. It downloads a checksum-verified native release binary for Linux x64, Linux ARM64, macOS ARM64, or Windows x64.
Build from source with the current stable Rust toolchain:
git clone https://github.com/dinglebear-ai/cortex.git
cd cortex mise install # optional, but pins the repository tools just build ./.cache/cargo/debug/cortex --version
The full daemon starts UDP and TCP syslog receivers plus the shared HTTP server. Use separate MCP and REST tokens:
mkdir -p "$HOME/.cortex/data"
export CORTEX_DB_PATH="$HOME/.cortex/data/cortex.db" export CORTEX_TOKEN="$(openssl rand -hex 32)" export CORTEX_API_TOKEN="$(openssl rand -hex 32)"
cortex serve mcp
Defaults:
0.0.0.0:1514 over UDP and TCP127.0.0.1:3100http://127.0.0.1:3100/mcphttp://127.0.0.1:3100/api/*http://127.0.0.1:3100/appVerify it from another terminal:
curl -fsS http://127.0.0.1:3100/health
logger -n 127.0.0.1 -P 1514 --tcp "cortex quickstart from $(hostname)"
export CORTEX_API_TOKEN="the-same-api-token" cortex tail --limit 10
For a managed local deployment, cortex setup repair creates or repairs the Cortex home, Compose assets, data paths, and missing 64-character MCP and REST tokens without replacing existing token values.
Query-only stdio mode reads the configured local database and starts no network listeners:
{
"mcpServers": { "cortex": { "command": "npx", "args": ["-y", "cortex-rmcp", "mcp"], "env": { "CORTEX_DB_PATH": "/absolute/path/to/cortex.db" } } } }
Streamable HTTP mode connects to the persistent daemon:
{
"mcpServers": { "cortex": { "url": "http://127.0.0.1:3100/mcp", "headers": { "Authorization": "Bearer your-cortex-token" } } } }
A useful first call is:
{"action":"status"}
Then narrow the investigation with tail, errors, search, timeline, or context before using broader analysis operations.
Cortex is one Rust binary with multiple operating modes. The same application and service layer backs the CLI, REST handlers, and MCP handlers, so validation, limits, identity resolution, redaction, and business rules do not belong to one transport alone.
INGESTION
Syslog UDP/TCP OTLP signals Docker agent / pull Managed file tails Heartbeats Claude / Codex / Gemini / Antigravity Shell history Agent commands Fleet inventory \ | / \ | / +---- bounded parsing and enrichment ----+ | scrub, normalize, batch | SQLite WAL + FTS5 | +----------------+----------------+ | | authoritative records derived accelerators logs, heartbeats, rollups, signatures, inventory, sessions graph projections | | +----------------+----------------+ | shared service layer | CLI REST MCP Web workspace
The daemon supervises its receivers and background services with cooperative cancellation. Shutdown drains HTTP requests, gives maintenance tasks 10 seconds to finish before abort-and-join, gives ingest 5 seconds to flush, and then attempts a WAL checkpoint. Already-running blocking SQLite calls cannot be cancelled by Tokio.
Background services include:
Heavy analytical reads and maintenance jobs have separate concurrency controls so one expensive investigation cannot starve the ingest path.
All log-like sources are normalized into the same durable log model, enriched where safe, scrubbed where configured, and written through bounded batch paths.
Cortex listens on the same configurable port for UDP and TCP syslog. It parses common RFC 3164 and RFC 5424 shapes, preserves the raw frame, records sender identity, normalizes severity and facility, and enriches known application formats.
Relevant defaults:
0.0.0.0:1514Syslog has no application-layer authentication. Restrict senders with network controls and CORTEX_ALLOWED_SOURCE_CIDRS when the listener is reachable beyond a trusted network.
Built-in enrichment recognizes useful signals from AdGuard, Authelia, Docker lifecycle events, fail2ban, Linux kernel and OOM events, SWAG, reverse-proxy logs, and host-local Cortex Docker agent metadata. Source gates can restrict enrichment that would otherwise trust a marker inside an unauthenticated syslog body.
Cortex accepts protobuf OTLP/HTTP export requests on the shared HTTP listener. Logs use POST /v1/logs with a 4 MiB body limit and flow through the normal writer. Metrics use POST /v1/metrics and traces use POST /v1/traces, each with an 8 MiB body limit and dedicated storage. Metric requests admit at most 5,000 points and also enforce a bounded normalized payload budget.
Current OTLP scope is intentionally narrow:
All three OTLP endpoints authenticate with `CORTEX_TOKEN` — the same static MCP bearer token that guards POST /mcp, read from the managed ~/.cortex/.env on a deployed host. It is not CORTEX_API_TOKEN (REST /api/*) and not CORTEX_API_ADMIN_TOKEN. Loopback and trusted-gateway policies skip the check. An OAuth-only deployment with no static token denies OTLP outright, because machine exporters have no OAuth flow — so a non-loopback OAuth-only OTLP exposure is rejected at startup unless CORTEX_TOKEN is set.
Cortex supports two Docker collection paths:
Central pull is disabled by default. The CORTEX_DOCKER_HOSTS shorthand expands hosts into insecure http://host:2375 endpoints and should only be used on a tightly controlled private network. A hosts file supports explicit base URLs and safer endpoint configuration.
Managed file-tail sources are persisted in a registry and supervised by the daemon. Add, remove, list, and inspect sources through the CLI, REST, or the file_tails MCP admin action.
The path policy rejects unsafe targets, including paths outside configured roots, symlink escap
只显示了开头部分;其余内容请在仓库中阅读