Supabase
Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.
Description from the maker (original English)
Self-hosted homelab log intelligence over MCP, CLI, and REST with SQLite/FTS.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
CORTEX_HOME, CORTEX_TOKEN, CORTEX_API_TOKEN, CORTEX_RMCP_VERSION, CORTEX_RMCP_REPO, CORTEX_RMCP_RELEASE_BASE_URL, RUST_LOGValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"cortex": {
"command": "npx",
"args": [
"-y",
"@dinglebear/cortex",
"mcp"
],
"env": {
"CORTEX_HOME": "your-value",
"CORTEX_TOKEN": "your-value",
"CORTEX_API_TOKEN": "your-value",
"CORTEX_RMCP_VERSION": "your-value",
"CORTEX_RMCP_REPO": "your-value",
"CORTEX_RMCP_RELEASE_BASE_URL": "your-value",
"RUST_LOG": "your-value"
}
}
}
}Run this in your terminal
claude mcp add cortex --env CORTEX_HOME=your-value --env CORTEX_TOKEN=your-value --env CORTEX_API_TOKEN=your-value --env CORTEX_RMCP_VERSION=your-value --env CORTEX_RMCP_REPO=your-value --env CORTEX_RMCP_RELEASE_BASE_URL=your-value --env RUST_LOG=your-value -- npx -y @dinglebear/cortex mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"cortex": {
"command": "npx",
"args": [
"-y",
"@dinglebear/cortex",
"mcp"
],
"env": {
"CORTEX_HOME": "your-value",
"CORTEX_TOKEN": "your-value",
"CORTEX_API_TOKEN": "your-value",
"CORTEX_RMCP_VERSION": "your-value",
"CORTEX_RMCP_REPO": "your-value",
"CORTEX_RMCP_RELEASE_BASE_URL": "your-value",
"RUST_LOG": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"cortex": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@dinglebear/cortex",
"mcp"
],
"env": {
"CORTEX_HOME": "your-value",
"CORTEX_TOKEN": "your-value",
"CORTEX_API_TOKEN": "your-value",
"CORTEX_RMCP_VERSION": "your-value",
"CORTEX_RMCP_REPO": "your-value",
"CORTEX_RMCP_RELEASE_BASE_URL": "your-value",
"RUST_LOG": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
CORTEX_HOME envCORTEX_RMCP_VERSION envCORTEX_RMCP_REPO envCORTEX_RMCP_RELEASE_BASE_URL envRUST_LOG envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified against the domain dinglebear.ai (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: CORTEX_TOKEN, CORTEX_API_TOKEN
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (3.13.2) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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
Only the beginning is shown; read the rest in the repo