Cortex RMCP
What it does
Rust MCP server for homelab logs, syslog, Docker logs, FTS search, and AI transcript correlation.
- Connects 在你的电脑上运行
- Account or key Needs CORTEX_TOKEN, CORTEX_API_TOKEN
- Category 开发者工具
安装
选择你使用的 AI 应用,然后复制设置。
通过 2/3 项检查 · 在你的电脑上运行
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
打开电脑版 Claude 应用的设置文件
SettingsDeveloperEdit Config
粘贴这些设置并保存文件
正在检查命令 · 通过后才会显示复制按钮
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
退出 Claude 再重新打开
试一试
用 Cortex RMCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Cortex RMCP,或回答中出现 Cortex RMCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Cortex RMCP
Cortex RMCP 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
你可以改用这些方式
A · 使用能连接 Cortex RMCP 的应用
- 需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
- 需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次)
- 需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次)
- 需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次)
B · 开发者工具 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
- Sentry✓ ChatGPT
- Compiler Explorer✓ ChatGPT
- GitDiagram✓ ChatGPT
可连接 Claude Code,但需要先准备
需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次)
打开终端
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
粘贴这条命令并按 Enter
正在检查命令 · 通过后才会显示复制按钮
按 Enter 前,把“your-value”改成你的密钥
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
在 Claude Code 中输入 /mcp
应能看到 Cortex RMCP 在列表中并显示已连接
试一试
用 Cortex RMCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Cortex RMCP,或回答中出现 Cortex RMCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor,但需要先准备
需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次)
点击这个按钮打开 Cursor
正在检查命令 · 通过后才会显示复制按钮
填写你的密钥
在 Cortex RMCP 的设置中,CORTEX_HOME, CORTEX_TOKEN, CORTEX_API_TOKEN, CORTEX_RMCP_VERSION, CORTEX_RMCP_REPO, CORTEX_RMCP_RELEASE_BASE_URL, RUST_LOG 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
在 Cursor 中以 Agent 模式打开 AI 聊天
试一试
用 Cortex RMCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Cortex RMCP,或回答中出现 Cortex RMCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code,但需要先准备
需要 Cortex RMCP 的密钥(在开发者网站创建) · 需要先在电脑上安装 Node.js(只需一次)
点击这个按钮打开 VS Code
正在检查命令 · 通过后才会显示复制按钮
填写你的密钥
在 Cortex RMCP 的设置中,CORTEX_HOME, CORTEX_TOKEN, CORTEX_API_TOKEN, CORTEX_RMCP_VERSION, CORTEX_RMCP_REPO, CORTEX_RMCP_RELEASE_BASE_URL, RUST_LOG 还是空的,填入你的密钥并保存
只把密钥粘贴到应用的输入框里,不要粘贴到聊天中或发给任何人
在 VS Code 中以 Agent 模式打开 AI 聊天
试一试
用 Cortex RMCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Cortex RMCP,或回答中出现 Cortex RMCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
开发者专用:终端命令和 JSON 设置
安装在电脑上
Claude Code
正在检查命令 · 通过后才会显示复制按钮
Claude Desktop (claude_desktop_config.json)
正在检查命令 · 通过后才会显示复制按钮
Cursor (~/.cursor/mcp.json)
正在检查命令 · 通过后才会显示复制按钮
VS Code (mcp.json)
正在检查命令 · 通过后才会显示复制按钮
需要你填写的值
CORTEX_HOMEenvOptional Cortex home directory containing configuration and local SQLite data.CORTEX_TOKEN机密 envOptional bearer token for Cortex MCP HTTP mode; also used by some shared configs.CORTEX_API_TOKEN机密 envBearer token for Cortex REST API routes when running daemon/API mode.CORTEX_RMCP_VERSIONenvOptional GitHub release tag override for the downloaded Cortex binary.CORTEX_RMCP_REPOenvOptional GitHub owner/repo override for release asset downloads.CORTEX_RMCP_RELEASE_BASE_URLenvOptional release download base URL override.RUST_LOGenvTracing filter for Cortex logs.
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。
一览
哪些应用可以使用它
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它能做什么
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。
基础检查i
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13日
- ! 注意
作者与仓库一致
发布者(dinglebear.ai)不是仓库所有者(dinglebear-ai);可能是其他人代为上架的
- ✓ 通过
仍在维护
代码最后更新于4天前
- ✓ 通过
有许可证
使用 AGPL-3.0
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
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
讨论
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
用户评价
还没有评价
与“开发者工具”中的其他服务器比较i
- 星标数多于此分类中其他 5822 个服务器的 0%
- 发布到注册中心的时间比此分类中其他 5822 个服务器的 20% 更新
- 基础检查结果等于或优于此分类中其他 5822 个服务器的 44%
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。
常见问题
Cortex RMCP 安全吗?
它在 3 项适用的基础检查中通过了 2 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。
它需要哪些密钥或代码?
你需要填写:CORTEX_TOKEN, CORTEX_API_TOKEN
它在我的电脑上运行还是在云端?
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)。
它还在维护吗?
GitHub 仓库最后更新于4天前,最新版本(3.9.1)于4个月前进入注册中心。
哪些应用可以使用它?
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。
同类别的其他选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Serena MCP: the IDE for your agent
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
作者的 README
打开 README
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。
Cortex
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.
At a glance
| 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.
Contents
- Quick start
- How Cortex is built
- Ingestion
- Investigation and intelligence
- Fleet inventory and graph
- AI session intelligence
- Alerts and notifications
- Interfaces
- Configuration
- Authentication and trust boundaries
- Storage and maintenance
- Deployment and distribution
- Operations
- Development and verification
- Documentation
- Current boundaries
- License
Quick start
Install the CLI
The first-class guided path is:
npx skills add dinglebear-ai/cortex --skill install-cortex
Start a fresh agent task and invoke $install-cortex. It chooses server or client-only role, delegates to the canonical installer/setup engine, configures auth/network/storage, and verifies the live client connection.
The npm launcher remains the fastest manual path for local CLI and stdio MCP use:
npx -y @dinglebear/cortex --help
npx -y @dinglebear/cortex mcp
Install it permanently with:
npm install --global @dinglebear/cortex
cortex --version
The launcher requires Node.js 18 or newer. It downloads a checksum-verified native release binary for Linux x64, Linux ARM64, macOS ARM64, or Windows x64.
Build from source with the current stable Rust toolchain:
git clone https://github.com/dinglebear-ai/cortex.git
cd cortex mise install # optional, but pins the repository tools just build ./.cache/cargo/debug/cortex --version
Start a local server
The full daemon starts UDP and TCP syslog receivers plus the shared HTTP server. Use separate MCP and REST tokens:
mkdir -p "$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:
- Syslog:
0.0.0.0:1514over UDP and TCP - HTTP:
127.0.0.1:3100 - MCP:
http://127.0.0.1:3100/mcp - REST:
http://127.0.0.1:3100/api/* - Investigation workspace:
http://127.0.0.1:3100/app
Verify 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.
Connect an MCP client
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.
How Cortex is built
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:
- Retention and storage-budget enforcement
- WAL and FTS maintenance
- Docker ingest supervision
- File-tail supervision
- Error-signature scanning
- Notification evaluation, dispatch, and digest scheduling
- Inventory refresh and backfill
- Graph projection refresh
- AI-session and timeline rollups
- Database optimization and maintenance jobs
Heavy analytical reads and maintenance jobs have separate concurrency controls so one expensive investigation cannot starve the ingest path.
Ingestion
All log-like sources are normalized into the same durable log model, enriched where safe, scrubbed where configured, and written through bounded batch paths.
Syslog over UDP and TCP
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:
- Bind:
0.0.0.0:1514 - Maximum message: 8 KiB
- Maximum concurrent TCP connections: 512
- TCP idle timeout: 300 seconds
- Writer batch: 100 records or 500 ms
- Write queue capacity: 10,000 records
Syslog 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.
OpenTelemetry ingestion
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:
- Logs, traces, and metrics over HTTP/protobuf are supported.
- OTLP/gRPC is not implemented.
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.
Docker logs and events
Cortex supports two Docker collection paths:
- Host-local agent, the preferred multi-host path. The host-local cortex agent reads the local Docker socket, converts logs and lifecycle events into bounded records, and forwards them to the server without changing Docker's daemon logging driver.
- Central pull compatibility mode, an optional server-side collector for explicitly configured Docker Engine or docker-socket-proxy HTTP endpoints. It records per-container checkpoints and reconnects with bounded exponential backoff.
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 tails
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