ssh-ide-mcp 2.0.0

SSH MCP Server — Connect to remote Linux servers, execute commands, manage files via AI agents

SSH IDE MCP

SSH MCP Server — Connect to remote Linux servers via SSH, execute commands, manage files, run Python/Jupyter code — all through AI agent conversation.

Features

• 🔌 SSH Connection — Key or password auth, persistent sessions
• 📋 Command Execution — Run any shell command on remote server
• 📁 File Operations — Read, write, edit, delete, list, glob, upload, download
• 🐍 Python Execution — Run Python code in any conda environment
• 📓 Jupyter Notebooks — Read, edit, execute notebook cells with persistent state
• 🖥️ Environment Management — List conda environments, switch Python versions
• 🤖 Universal MCP — Works with Reasonix, Cursor, Claude Code, Codex, and any MCP client

Installation

pip install ssh-ide-mcp

Quick Start

1. Start MCP Server

ssh-ide-mcp mcp

2. Configure your AI Agent

Reasonix (.mcp.json at project root):

{
  "ssh-ide-mcp": {
    "command": "ssh-ide-mcp",
    "args": ["mcp"],
    "env": {}
  }
}

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "ssh-ide-mcp": {
      "command": "ssh-ide-mcp",
      "args": ["mcp"]
    }
  }
}

Claude Code (~/.claude/settings.json or claude.json):

{
  "mcpServers": {
    "ssh-ide-mcp": {
      "command": "ssh-ide-mcp",
      "args": ["mcp"]
    }
  }
}

Codex CLI (add to your MCP config):

{
  "ssh-ide-mcp": {
    "command": "ssh-ide-mcp",
    "args": ["mcp"]
  }
}

3. Connect to your server

Tell your AI agent:

"SSH connect to 192.168.1.100 as root, password: mypassword, workdir: /home/project"

Or use key auth:

"SSH connect to 10.0.0.1 as deploy, key: ~/.ssh/id_rsa, workdir: /var/www"

Available Tools (24 tools)

Category	Tools
Connection	ssh_connect, ssh_disconnect, ssh_connections, ssh_save_host, ssh_connect_saved, ssh_list_hosts
Command	ssh_exec
Files	ssh_read_file, ssh_write_file, ssh_edit_string, ssh_delete_range
Directory	ssh_ls, ssh_glob, ssh_stat, ssh_file_tree
Transfer	ssh_download, ssh_upload
Python	ssh_execute_python, ssh_list_environments
Notebook	ssh_read_notebook, ssh_execute_notebook_cell, ssh_edit_notebook_cell, ssh_add_notebook_cell, ssh_delete_notebook_cell

Example Workflow

1️⃣ Connect →  ssh_connect(hostname="...", username="...", password="...", host_alias="my-server")
2️⃣ Explore →  ssh_ls(host_alias="my-server", path="/home/project")
3️⃣ Read    →  ssh_read_file(host_alias="my-server", path="/home/project/config.yml")
4️⃣ Edit    →  ssh_edit_string(host_alias="my-server", path="/home/project/config.yml",
                                 old_string="version: 1", new_string="version: 2")
5️⃣ Execute →  ssh_exec(host_alias="my-server", command="python3 train.py")
6️⃣ Python  →  ssh_execute_python(host_alias="my-server", code="import torch; print(torch.__version__)", python_bin="python3")
7️⃣ Disconnect → ssh_disconnect(host_alias="my-server")

Requirements

• Python 3.9+
• Remote server: SSH access

Configuration

Host configs saved at ~/.ssh-ide-mcp/config.json.

License

MIT