ellmos ServerCommander

Name: ellmos ServerCommander
Author: ellmos-ai

by ellmos-aiversion 0.1.0-alpha.20i★ –iRuns on your computer

Registry nameio.github.ellmos-ai/ellmos-servercommander-mcp

Install

Overview

Description from the maker (original English)

Server operations MCP: HTTP health checks, log analysis, deploy dry-runs, mail diagnostics.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiEarly↓ 395/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Clinics & health

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "ellmos-servercommander": {
      "command": "npx",
      "args": [
        "-y",
        "ellmos-servercommander-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add ellmos-servercommander -- npx -y ellmos-servercommander-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "ellmos-servercommander": {
      "command": "npx",
      "args": [
        "-y",
        "ellmos-servercommander-mcp"
      ]
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ellmos-servercommander": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "ellmos-servercommander-mcp"
      ]
    }
  }
}

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.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account ellmos-ai, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Clinics & healthi

More stars than 0% of the other 1028 servers in this category
Published to the registry more recently than 65% of the other 1028 servers in this category
Basic checks equal to or better than 100% of the other 1028 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is ellmos ServerCommander safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0-alpha.20) reached the registry 14 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Mirobody, FHIR MCP Server, Google Health MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Mirobody

Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.

by thetahealthGrowing↓ 290/wk★ 1.4KUpdated yesterday

Runs on your computer✓ thetahealth.ai

Install

FHIR MCP Server

MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications

by wso2Growing↓ 823/wk★ 137Updated 10 days ago

Runs on your computer

Install

Google Health MCP

Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents

by davidmosiahGrowing↓ 1K/wk★ 79Updated 4 months ago

Runs on your computer

Install

README from the maker

Open the README

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.

ellmos-servercommander-mcp

Alpha Model Context Protocol (MCP) server for local-first server operations: deployment dry-runs, mail configuration status, access-log analysis, and resilient HTTP health checks.

German README: README_de.md

*Part of the ellmos-ai family under the open-bricks open-source umbrella.*

-blue.svg)

[!NOTE]

Discoverability & AI Search: Published on npm as ellmos-servercommander-mcp, cataloged for MCP ecosystems in server.json, glama.json, and smithery.yaml, and indexed for AI/LLM search in llms.txt.

Quick Navigation

Executive Summary & Core Identity
Visual Architecture & System Topology
Operations Lifecycle & Execution Sequence Flow
Target Personas & High-Intent SEO Queries
Comparative Matrix vs. Alternatives
Key Capabilities & Safety Invariants
Start Here & Quick Guidance
Status & Protocol Support
Installation & Prerequisites
MCP Client Configuration & Deployment Modes
Configuration & Profiles Specification
Tools & Handlers Reference
Search, Disambiguation & Discovery Keywords
Sibling Ecosystem Matrix
Third-Party Licenses & Level 1 SBOM
Security Policy & Operational Limits (48h SLA)
Development, Verification & CI Matrix
Statutory Notice, Liability Limitation & License (§ 521 BGB)

1. Executive Summary & Core Identity

ellmos-servercommander-mcp is an authoritative, local-first Model Context Protocol (MCP) server engineered specifically for AI coding assistants and autonomous agent platforms (Claude Code, Cursor, Codex, Antigravity, Gemini). It enables agents to safely diagnose server health, analyze web server access logs, inspect mail readiness, and build dry-run deployment plans without exposing production infrastructure to unverified, destructive mutations or arbitrary shell execution.

Every operation is governed by strict local-first and zero-elevation guarantees:

100% Local-First & Zero-Egress by Default: Diagnostic parsing and manifest hashing execute locally; zero telemetry and zero unverified outbound network requests.
Dry-Run & Staging First: Deployment operations calculate SHA-256 tree digests and check target profiles before any remote command is staged.
Unprivileged Execution (`RunAsInvoker`): Operates within standard unprivileged user space without requiring root or administrator elevation.

2. Visual Architecture & System Topology

The following diagram illustrates the decoupled layers of ServerCommander, from MCP host transport and Node.js process supervision to Python dispatching, operational engines, and local persistence sinks:

flowchart TD

subgraph HostLayer ["1. MCP Host & AI Client Layer"] Host["MCP Host: Claude Desktop / Claude Code / Cursor"] end

subgraph GatewayLayer ["2. Gateway & Process Supervision Layer"] NodeWrapper["Node.js CLI Wrapper (bin/ellmos-servercommander.js)"] end

subgraph CoreLayer ["3. Python MCP Server Core Layer"] FastMCP["Python MCP Server (FastMCP Transport stdio)"] Dispatcher["Tool Dispatcher & Parameter Validator"] i18nEngine["i18n Translation Engine (en, de, es, zh, ja, ru)"] end

subgraph OperationsLayer ["4. Operations & Diagnostics Engines"] HTTPProbe["HTTP Health Probe (sc_health_check)"] LogAnalyzer["Apache/Nginx Log Analyzer (sc_logs_analyze)"] DeployStaging["Deployment Staging & Manifest Planner (sc_deploy / sc_deploy_status)"] MailDiagnostics["IMAP/SMTP Safety Diagnostics (sc_mail_*)"] end

subgraph SinkLayer ["5. Local Storage & Audit Sink Layer"] SQLiteHist[("Local SQLite Deploy History (deploy-history.db)")] JSONReports[("Sanitized JSON Log Reports")] AuditSink["Local Diagnostic Outputs & Stdout Stream"] end

Host <-->|"stdio / JSON-RPC"| NodeWrapper NodeWrapper <-->|"Child Process Stdio"| FastMCP FastMCP --> Dispatcher Dispatcher <--> i18nEngine Dispatcher --> HTTPProbe Dispatcher --> LogAnalyzer Dispatcher --> DeployStaging Dispatcher --> MailDiagnostics DeployStaging -.->|"Optional opt-in persist"| SQLiteHist LogAnalyzer -.->|"Optional persist_report"| JSONReports HTTPProbe -.-> AuditSink MailDiagnostics -.-> AuditSink

ASCII Architectural Topology (Four-View Projection)

========================================================================================

ellmos-servercommander-mcp: Four-View Architectural Topology ========================================================================================

[VIEW 1: COMPONENT STRUCTURE & TRANSPORT BOUNDARIES] +----------------------------------------------------------------------------------+ | 1. MCP Host & AI Client (Claude Desktop / Claude Code / Cursor / Codex) | | - Stdio JSON-RPC transport protocol | +----------------------------------------------------------------------------------+ | | (JSON-RPC via stdio stream) v +----------------------------------------------------------------------------------+ | 2. Gateway & Process Supervision (bin/ellmos-servercommander.js) | | - Node.js CLI launcher & process supervisor (update-notifier checks) | | - Working directory isolation: PYTHONSAFEPATH=1 prevents rogue import hijack | +----------------------------------------------------------------------------------+ | | (Supervised child process stdio) v +----------------------------------------------------------------------------------+ | 3. FastMCP Dispatcher & i18n Localization Engine (src/servercommander/) | | - FastMCP server lifecycle, tool schema generation & parameter validation | | - Multi-language localization engine (6 locales: en, de, es, zh, ja, ru) | +----------------------------------------------------------------------------------+

[VIEW 2: OPERATIONAL ENGINES & DRY-RUN EXECUTION] +----------------------------------------------------------------------------------+ | 4. Tool Handlers & Diagnostic Engines | | - sc_health_check: Non-blocking HTTP/HTTPS probe with timeout & batch error | | - sc_logs_analyze: Sanitized Apache/Nginx access-log parser & threat detector| | - sc_deploy / sc_deploy_status: Fail-safe SHA-256 tree hashing & dry-run plan| | - sc_mail_list / sc_mail_read / sc_mail_send: Dry-run IMAP/SMTP diagnostics | +----------------------------------------------------------------------------------+

[VIEW 3: LOCAL PERSISTENCE & CONCURRENCY MODEL] +----------------------------------------------------------------------------------+ | 5. Local Storage & Audit Sinks | | - Local SQLite Deploy History (deploy-history.db) with explicit lease release | | - Sanitized JSON diagnostic reports (optional persist_report) | | - Thread-isolated HTTP GET workers preventing event-loop stalling | +----------------------------------------------------------------------------------+

[VIEW 4: SECURITY BOUNDARY & ZERO-EGRESS PERIMETER] +----------------------------------------------------------------------------------+ | 6. Governance & Defense Invariants (INV-LOCAL-01 through INV-SLA-10) | | - RunAsInvoker: 100% unprivileged user mode; zero root/sudo/UAC requirement | | - Zero-Egress by default: zero telemetry, zero unverified background outbound | | - Safe Process Isolation: cwd package exclusion, sanitized error messages | | - 48h Response SLA & statutory liability limitation (§ 521 BGB) | +----------------------------------------------------------------------------------+ ========================================================================================

3. Operations Lifecycle & Execution Sequence Flow

The following sequence diagram demonstrates the lifecycle of operations dispatched by an AI agent through ServerCommander, showing concurrent HTTP probing, log parsing, and dry-run manifest calculation:

sequenceDiagram

autonumber actor User as AI Assistant / User participant Host as MCP Host (Claude / Cursor) participant Wrapper as Node.j

Only the beginning is shown; read the rest in the repo

ellmos ServerCommander

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Clinics & healthi

Common questions

Alternatives

Mirobody

FHIR MCP Server

Google Health MCP

README from the maker

ellmos-servercommander-mcp

Quick Navigation

1. Executive Summary & Core Identity

2. Visual Architecture & System Topology

ASCII Architectural Topology (Four-View Projection)

3. Operations Lifecycle & Execution Sequence Flow