Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

ssh-mcp

by gelseversion 0.3.0i★ –iRuns on your computer
Registry nameio.github.gelse/ssh-mcp

Install

Overview

Description from the maker (original English)

MCP gateway for controlled SSH access with per-client auth, command policies, and audit logging.

PopNx MCP’s three pillars

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

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: Streamable HTTP
  • Category: Other
  • You need to fill in: CONFIG_API_TOKEN

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).
  • You fill in yourself: CONFIG_DIR, LOG_DIR, CONFIG_API_ENABLED, CONFIG_API_TOKEN

Values 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": {
    "ssh": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CONFIG_DIR",
        "-e",
        "LOG_DIR",
        "-e",
        "CONFIG_API_ENABLED",
        "-e",
        "CONFIG_API_TOKEN",
        "ghcr.io/gelse/ssh-mcp:0.3.0"
      ],
      "env": {
        "CONFIG_DIR": "your-value",
        "LOG_DIR": "your-value",
        "CONFIG_API_ENABLED": "your-value",
        "CONFIG_API_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add ssh --env CONFIG_DIR=your-value --env LOG_DIR=your-value --env CONFIG_API_ENABLED=your-value --env CONFIG_API_TOKEN=your-value -- docker run -i --rm -e CONFIG_DIR -e LOG_DIR -e CONFIG_API_ENABLED -e CONFIG_API_TOKEN ghcr.io/gelse/ssh-mcp:0.3.0

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "ssh": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CONFIG_DIR",
        "-e",
        "LOG_DIR",
        "-e",
        "CONFIG_API_ENABLED",
        "-e",
        "CONFIG_API_TOKEN",
        "ghcr.io/gelse/ssh-mcp:0.3.0"
      ],
      "env": {
        "CONFIG_DIR": "your-value",
        "LOG_DIR": "your-value",
        "CONFIG_API_ENABLED": "your-value",
        "CONFIG_API_TOKEN": "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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ssh": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CONFIG_DIR",
        "-e",
        "LOG_DIR",
        "-e",
        "CONFIG_API_ENABLED",
        "-e",
        "CONFIG_API_TOKEN",
        "ghcr.io/gelse/ssh-mcp:0.3.0"
      ],
      "env": {
        "CONFIG_DIR": "your-value",
        "LOG_DIR": "your-value",
        "CONFIG_API_ENABLED": "your-value",
        "CONFIG_API_TOKEN": "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.

Values you fill in

  • CONFIG_DIR env
    Directory containing ssh-mcp-config.json
  • LOG_DIR env
    Directory for JSONL audit logs
  • CONFIG_API_ENABLED env
    Enable the configuration REST API and web dashboard
  • CONFIG_API_TOKEN secret env
    Bearer token for the configuration API

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 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account gelse, 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 Otheri

  • More stars than 0% of the other 32410 servers in this category
  • Published to the registry more recently than 43% of the other 32410 servers in this category
  • Basic checks equal to or better than 100% of the other 32410 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 ssh-mcp 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?

You need to fill in: CONFIG_API_TOKEN

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 (0.3.0) reached the registry 2 months ago.

Which apps can use it?

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

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, debuff

Alternatives

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

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
Install

debuff

by debuffjp

Let coding agents play, test and tune your 2D web game: live state, explained errors, replays, fuzz.

Runs on your computerUpdated today
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.

ssh-mcp

A centralized MCP gateway that gives AI agents controlled SSH access over Streamable HTTP.


What problem does this solve?

Most MCP SSH servers run as local stdio processes — one per client, with no shared state, no centralized authorization, and no audit trail. When multiple AI agents need SSH access, each manages its own SSH keys and runs its own process. This creates:

  • No centralized access control — every client decides what it can run
  • No audit trail — commands are invisible to the ops team
  • SSH key sprawl — keys scattered across every agent machine
  • No rate limiting — a runaway agent can overwhelm a target

ssh-mcp solves this by deploying a single HTTP gateway. All clients connect to it; it connects to your SSH targets. Authorization, rate limiting, connection pooling, and audit logging happen in one place.


Quick Start

Using the pre-built image (recommended)
docker compose pull

docker compose up -d

The image is published at ghcr.io/gelse/ssh-mcp:latest. The compose file maps host port 9080 to container port 8080.

Verify the server is running:

curl http://localhost:9080/health

→ {"status": "ok"}

Create a minimal config in config/ssh-mcp-config.json:

{

"version": 1, "ssh_targets": { "my-server": { "host": "10.0.1.10", "username": "deploy" } }, "allowed_commands": { "default": [ { "targets": ["*"], "commands": ["hostname", "uptime", "free", "df"] } ] } }

Generate an API key hash and add it to your config or secrets.json (see Configuration).

Build locally instead

make build

docker compose up -d --build

</details>

What you can do (tools)

Six MCP tools are available over Streamable HTTP:

ToolDescription
ssh_list_serversList configured SSH targets
ssh_list_allowed_commandsShow allowed commands for a target
ssh_execute_commandExecute a command on a remote server
ssh_check_connectionTest SSH connectivity to a target
ssh_download_fileDownload a file via SFTP
ssh_upload_fileUpload a file via SFTP
Tool Naming Convention

All tools follow the pattern ssh_ _ :

  • ssh_list_servers — list resources
  • ssh_list_allowed_commands — list permissions
  • ssh_execute_command — perform an action
  • ssh_check_connection — verify connectivity
  • ssh_download_file / ssh_upload_file — file transfer

See examples/README.md for usage examples including curl commands and Python client code.


What's configurable

ssh-mcp is configured via JSON files with hot-reload (15 s poll, 2 s debounce). Key areas:

AreaDetails
SSH targetsHost, port, username, key, password
Command policiesBlock patterns, per-key/network allowlists
Connection poolMax connections, idle timeout, concurrency
Rate limitingPer-IP sliding window (default 60 req/min)
LoggingJSONL with rotation, gzip, multiple targets
SFTPSandbox root, path length limits

Full reference: docs/CONFIGURATION.md

FilePurpose
ssh-mcp-config.jsonMain config
config.schema.jsonJSON Schema for validation
secrets.jsonPasswords and API key hashes
MCP_SSH_* env varsOverrides for any setting

Why not just raw SSH / other MCP servers?

ssh-mcp adds a layered authorization chain (9 ordered layers) between every client request and every SSH command. Per-API-key and per-network rules let different agents get different permissions on different servers — without touching the underlying SSH accounts.

Additional protections:

  • Circuit breakers isolate failing targets with exponential backoff
  • Rate limiting prevents runaway agents from overwhelming hosts
  • Structured audit logs trace every command, client, IP, and authorization decision
  • Connection pooling reuses SSH sessions across requests
  • Input sanitization and dangerous-pattern detection block shell injection attempts

Architecture: ARCHITECTURE.md Security model: docs/SECURITY.md


What it is NOT

  • Not an interactive shell — commands are executed individually with structured output
  • Not a file manager — SFTP supports single-file download and upload only (no directory listing or recursive transfer)
  • Not a firewall / network ACL — authorization is command-level, not network-level
  • Does not reduce SSH account privileges — if a command is allowed, the SSH user executes it with whatever privileges that account has

Not yet / known gaps

Fixable with contribution:

  • SFTP is single-file only — no directory listing or recursive transfer
  • No TLS termination — run Traefik or nginx in front
  • No OAuth or mTLS app-layer authentication
  • Rate limiter settings are not hot-reloadable (set at boot)

Architectural:

  • Config API dashboard login sessions are in-memory only — they don't survive restarts and the API is single-instance (config changes themselves persist to the config file normally)
  • No tamper protection for audit logs

Observability

  • Health: GET /health — returns {"status": "ok"}
  • Metrics: GET /metrics — Prometheus exposition format
  • Logging: Structured JSONL with request correlation

Full reference: docs/OBSERVABILITY.md


Config API & Dashboard

An optional web dashboard for managing configuration without editing JSON files. Enable with CONFIG_API_ENABLED=true.

Full reference: docs/CONFIG-API.md


FAQ

Dashboard returns 401 over HTTP

The session cookie defaults to Secure (HTTPS only). For local HTTP testing, set:

environment:
  • CONFIG_API_SESSION_COOKIE_SECURE=false

Then restart the container.

How do MCP clients connect?

Connect to http://host:9080/mcp using the Streamable HTTP transport. Pass your API key via X-API-Key or Authorization: Bearer header.

How do I generate an API key hash?
docker compose exec mcp-ssh python -c \

"from lib.crypto import hash_api_key; print(hash_api_key('your-key'))"

→ pbkdf2:sha256:100000$ $

Or use the hash utility in the Config API dashboard.

How does hot reload work?

The config file is polled every 15 seconds with a 2-second debounce. Changes to targets, commands, and settings take effect without restart. Rate limiter and log target settings require a restart.

Why was my command denied?

Commands are evaluated through a 9-layer authorization chain. The matched_via field in logs shows which layer denied. See Security Model for the full chain.

How does rate limiting work?

Per-IP sliding window, default 60 requests per 60 seconds. Exceeding the limit returns HTTP 503. Configure via settings.rate_limit in the config file.

Where do logs go?

Logs are written to the /logs volume (mapped from ./logs). The active log file is ssh-mcp.log in JSONL format with optional gzip rotation.

Troubleshooting basics
# Check server health

curl http://localhost:9080/health

Validate config

make config-test

Check logs

docker compose logs mcp-ssh


Documentation

DocumentDescription
ARCHITECTURE.mdSystem design and data flow
docs/SECURITY.mdSecurity model and threat analysis
docs/CONFIGURATION.mdFull config reference
docs/CONFIG-API.mdConfig API & dashboard
docs/OBSERVABILITY.mdHealth, metrics, logging
CONTRIBUTING.mdDevelopment and contribution guide
CHANGELOG.mdRelease history
examples/Config examples and client code

Development

# Unit tests

make test

Integration tests (builds Docker image)

make integrationtest

See CONTRIBUTING.md for the full development guide, coding conventions, and PR workflow.


Roadmap

No public roadmap. See Not yet / known gaps for current limitations and opportunities.


License

MIT

Ask PopNx