Which integrations are available for this server?

Provides tools to execute commands, manage files, services, and packages on remote Linux servers via SSH.

How do I use MCP SSH Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP SSH Server run 'df -h' on prod-web-01" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP SSH Server

by Maxim11111

Overview Schema Related Servers Score Discussions

Python

Remote

MCP SSH Server

Remote SSH Management Server for LLM Agents

A centralized MCP (Model Context Protocol) server that enables LLM agents (Cursor AI, Claude Desktop, Codex, etc.) to securely execute commands and manage Linux servers via SSH.

License: MIT Python 3.10+

Features

🔐 Secure SSH Access - Key-based authentication with automatic setup
🌐 Official MCP SDK - Streamable HTTP (modelcontextprotocol/python-sdk)
🔏 MCP OAuth (RFC 9728) - Protected resource metadata + browser login for Claude Code; same API tokens as Bearer
🔄 Real-time Streaming - Live stdout/stderr streaming via SSE
🔑 Token-based Auth - Bearer tokens with granular permissions
🛡️ Security First - Command validation, rate limiting, audit logging
📊 Multi-server Support - Manage hundreds of servers from one endpoint
🚀 Production Ready - Docker support, health checks, graceful shutdown
🛠️ CLI Management - Easy server/token management via CLI tool

Related MCP server: ssh-mcp-server

Quick Start

Using Docker (Recommended)

# Clone repository
git clone https://github.com/Maxim11111/mcp-ssh.git
cd mcp-ssh

# Copy example configs
cp config/servers.json.example config/servers.json
cp config/tokens.json.example config/tokens.json

# Copy environment configuration
cp env.example .env

# Edit .env file to customize settings (optional)
# nano .env

# Start with Docker Compose
docker-compose up -d

# Quick view servers list
docker exec -it mcp-ssh-server python -m src.cli server list

# Add your first server
docker exec -it mcp-ssh-server python -m src.cli server add

# Check status
docker-compose logs -f mcp-ssh-server

Local Installation

# Install dependencies
pip install -r requirements.txt

# Setup configuration
mkdir -p config keys logs
cp config/servers.json.example config/servers.json
cp config/tokens.json.example config/tokens.json

# Add server
python -m src.cli server add

# Start server (factory loads env each process)
uvicorn src.server_http:create_app --factory --host 0.0.0.0 --port 8000

Architecture

[Cursor / Claude Code / Codex / …]
         ↓
  HTTPS → Streamable HTTP POST /mcp (Bearer or OAuth access token)
         ↓
  [MCP SSH Server] → SSH Keys → [Your Linux Servers]
         ↓
  Audit Logs + Security Validation

Set PUBLIC_BASE_URL in .env to the URL clients use (e.g. https://mcp.example.com behind TLS). The SDK publishes OAuth discovery at /.well-known/oauth-protected-resource/mcp and authorization server metadata at /.well-known/oauth-authorization-server. Browser login for MCP OAuth is at /login (paste the same API token you would put in Authorization: Bearer).

Client configuration (quick reference)

Client	Config	Notes
Cursor	`~/.cursor/mcp.json`	`url` + `headers.Authorization: Bearer tok_…`
Claude Code	`claude mcp add …` or project config	Use HTTP transport URL ending in `/mcp`; complete Authenticate with token from `cli token create`, or pre-supply Bearer if the client supports it
OpenAI Codex	`~/.codex/config.toml` or `.codex/config.toml`	`[mcp_servers.name]` with `url = "https://host/mcp"` and `bearer_token_env_var = "MCP_SSH_TOKEN"` (or `http_headers`) — see Codex MCP
Google Gemini CLI	`gemini mcp add …`	HTTP URL ending in `/mcp`; `-s user` = user-level config; Bearer via `--header "Authorization: Bearer tok_…"` or OAuth with `/mcp auth <name>`
Stdio	process env	`MCP_TOKEN=tok_…` and `python -m src.server_stdio`

Usage Examples

With Cursor AI

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "ssh-devops": {
      "url": "http://your-server:8000/mcp",
      "headers": {
        "Authorization": "Bearer tok_your_token_here"
      }
    }
  }
}

Then in Cursor chat:

You: Install nginx on prod-web-01
AI: Executing command on prod-web-01...
✓ nginx installed successfully

With Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "ssh-devops": {
      "url": "http://your-server:8000/mcp",
      "headers": {
        "Authorization": "Bearer tok_your_token_here"
      }
    }
  }
}

With Claude Code (CLI)

After the server is reachable at PUBLIC_BASE_URL (HTTPS in production):

claude mcp add --transport http ssh-devops https://your-server.example.com/mcp

Use Authenticate in /mcp when prompted: open /login, paste the API token from python -m src.cli token create. The issued access token is the same string as your Bearer token.

With Google Gemini CLI

Add a streamable HTTP server (user-wide config under ~/.gemini/):

gemini mcp add devops https://your-server.example.com/mcp --transport http -s user

If you use a Bearer token instead of the browser OAuth flow, pass it when adding the server:

gemini mcp add devops https://your-server.example.com/mcp --transport http -s user \
  --header "Authorization: Bearer tok_your_token_here"

With MCP OAuth, add the server first, then in the interactive CLI run /mcp auth devops (browser redirect to http://localhost:7777/oauth/callback).

With OpenAI Codex (`config.toml`)

[mcp_servers.ssh_devops]
url = "https://your-server.example.com/mcp"
bearer_token_env_var = "MCP_SSH_TOKEN"

Then export MCP_SSH_TOKEN=tok_... before running Codex.

Stdio (local)

export MCP_TOKEN=tok_your_token_here
export CONFIG_DIR=./config
python -m src.server_stdio

Available Tools

MCP SSH Server provides these tools to agents:

execute_command - Execute shell command on a server
execute_on_multiple - Execute command on multiple servers in parallel
read_file - Read file contents
write_file - Write/update files
list_directory - List directory contents
check_service_status - Check systemd service status
install_package - Install packages (apt/yum/dnf)
list_servers - Get available servers
get_system_info - Get system information

CLI Management

Server Management

# Add server with automatic SSH key setup
python -m src.cli server add

# List all servers
python -m src.cli server list

# Test connection
python -m src.cli server test prod-web-01

# Remove server
python -m src.cli server remove prod-web-01

Token Management

# Create new API token
python -m src.cli token create

# List tokens
python -m src.cli token list

# Revoke token
python -m src.cli token revoke tok_abc123

Configuration

Environment Variables (.env)

The server can be configured using environment variables. Copy env.example to .env and customize:

# Copy example configuration
cp env.example .env

# Edit configuration
nano .env

Key configuration options:

# Server Configuration
HOST=0.0.0.0                    # Server bind address
PORT=8000                       # Internal container port
EXTERNAL_PORT=8000              # External Docker host port

# Security
TOKEN_EXPIRY_HOURS=8760        # Token validity period

# Rate Limiting
RATE_LIMIT_PER_MINUTE=60       # Requests per minute
RATE_LIMIT_PER_HOUR=500        # Commands per hour

# SSH Settings
SSH_CONNECTION_TIMEOUT=30       # SSH connection timeout
SSH_COMMAND_TIMEOUT=300        # Command execution timeout

Reverse Proxy Setup

For production deployments with reverse proxy (nginx-proxy-manager, traefik, etc.):

# Use proxy compose file (recommended)
docker-compose -f docker-compose.yml -f docker-compose.proxy.yml up -d

servers.json

{
  "servers": {
    "prod-web-01": {
      "host": "192.168.1.10",
      "port": 22,
      "user": "deploy",
      "ssh_key_path": "/app/keys/prod_web_ed25519",
      "tags": ["production", "web"],
      "enabled": true,
      "description": "Production web server"
    }
  },
  "security": {
    "allowed_commands_patterns": ["^apt ", "^systemctl ", "^docker "],
    "forbidden_commands": ["rm -rf /", "mkfs"],
    "rate_limit": {
      "requests_per_minute": 60,
      "commands_per_hour": 500
    }
  }
}

tokens.json

{
  "tokens": {
    "tok_abc123...": {
      "name": "cursor-admin",
      "permissions": ["execute", "read", "write", "install"],
      "allowed_servers": ["*"],
      "rate_limit_multiplier": 1.0,
      "enabled": true
    }
  }
}

Security

Multi-layer Security

Bearer Tokens - API access control
SSH Keys - Server authentication (keys never leave server)
Command Validation - Whitelist/blacklist patterns
Rate Limiting - Per-token request limits
Audit Logging - All operations logged
Permission System - Granular access control

Best Practices

Use ED25519 SSH keys
Rotate tokens regularly
Configure allowed command patterns
Monitor audit logs
Use HTTPS in production (via nginx-proxy-manager)
Limit token permissions to minimum required

Testing

# Install dev dependencies
pip install -r requirements-dev.txt

# Run tests
pytest

# Run with coverage
pytest --cov=src --cov-report=html

# View coverage report
open htmlcov/index.html

See TESTING.md for detailed testing instructions.

Deployment

See DEPLOYMENT.md for production deployment guide.

Documentation

QUICKSTART.md - Quick start (RU/EN)
DEPLOYMENT.md - Production deployment guide
CURSOR_INTEGRATION.md - Cursor AI integration
DEVELOPMENT.md - Development and debugging
MCP_PROTOCOL.md - MCP protocol and tools
SECURITY.md - Security best practices
TESTING.md - Testing guide

API Endpoints

The server runs HTTP JSON-RPC on a single endpoint (see MCP_PROTOCOL.md):

MCP Protocol

GET /mcp - Server info and available transports
POST /mcp - JSON-RPC (methods: initialize, tools/list, tools/call)
GET /sse - SSE transport (legacy)

Utility

GET /health - Health check

Environment Variables

All configuration can be managed via .env file. See env.example for all available options:

# Server Configuration
HOST=0.0.0.0              # Listen host
PORT=8000                 # Internal container port
EXTERNAL_PORT=8000        # External Docker host port
LOG_LEVEL=INFO            # Logging level

# Directory Configuration
CONFIG_DIR=/app/config    # Configuration directory
KEYS_DIR=/app/keys        # SSH keys directory
LOGS_DIR=/app/logs        # Logs directory

# Security Settings
TOKEN_EXPIRY_HOURS=8760   # Token validity period

# Rate Limiting
RATE_LIMIT_ENABLED=true   # Enable rate limiting
RATE_LIMIT_PER_MINUTE=60  # Requests per minute
RATE_LIMIT_PER_HOUR=500   # Commands per hour

# SSH Settings
SSH_CONNECTION_TIMEOUT=30  # SSH connection timeout
SSH_COMMAND_TIMEOUT=300   # Command execution timeout

# Development Settings
DEBUG=false               # Debug mode
RELOAD=false              # Auto-reload on changes

Requirements

Python 3.10+
Docker & Docker Compose (for containerized deployment)
SSH access to target servers
OpenSSH client

Contributing

Contributions welcome! Please:

Fork the repository
Create a feature branch
Add tests for new features
Ensure all tests pass
Submit a pull request

License

MIT License - see LICENSE file for details.

Support

GitHub Issues: Report bugs
Documentation: See *.md files in the repository root
Email: your.email@example.com

Acknowledgments

Built with FastAPI
MCP Protocol specification by Anthropic
SSH via Paramiko
SSE streaming via sse-starlette

Made with ❤️ for the LLM DevOps community

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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MCP SSH Server

Features

Quick Start

Using Docker (Recommended)

Local Installation

Architecture

Client configuration (quick reference)

Usage Examples

With Cursor AI

With Claude Desktop

With Claude Code (CLI)

With Google Gemini CLI

With OpenAI Codex (config.toml)

Stdio (local)

Available Tools

CLI Management

Server Management

Token Management

Configuration

Environment Variables (.env)

Reverse Proxy Setup

servers.json

tokens.json

Security

Multi-layer Security

Best Practices

Testing

Deployment

Documentation

API Endpoints

MCP Protocol

Utility

Environment Variables

Requirements

Contributing

License

Support

Acknowledgments

Maintenance

Resources

Looking for Admin?

Latest Blog Posts

MCP directory API

With OpenAI Codex (`config.toml`)