MCP ShellKeeper

MCP ShellKeeper

Enables AI assistants to maintain persistent SSH terminal sessions and transfer files to/from remote servers. Allows stateful command execution, natural language server management, and seamless file operations through SSH connections.

Category
Visit Server

README

🐚 MCP ShellKeeper

<div align="center">

Persistent Terminal Sessions + File Transfer for AI Assistants

SSH into servers, run commands, transfer files — all through your AI assistant. No more stateless limitations.

License: MIT Node Version MCP npm npm downloads

Real-World ExampleInstallationCore FeaturesUse CasesTools

</div>


🎯 The Problem

AI assistants like Cursor execute commands statelessly — each command runs in a fresh environment:

❌ ssh user@server                          # Hangs forever - no output until exit
❌ Can't run commands after SSH
❌ Each command starts from scratch
❌ No way to transfer files to/from servers
❌ Must re-authenticate for every operation

✨ The Solution

ShellKeeper transforms AI assistants into stateful operators with persistent sessions and file transfer capabilities.


🚀 Core Features

<table> <tr> <td width="33%" align="left">

🔄 Stateful Execution

Traditional AI (Stateless)

You: "SSH to server"
AI: ❌ Command hangs forever

You: "List files"
AI: ❌ Runs on local, not server

ShellKeeper (Stateful)

You: "Connect to my server"
AI: ✅ Establishes SSH session

You: "What files are there?"
AI: ✅ Lists files on server

You: "Go to the logs folder"
AI: ✅ Changes to /var/log

You: "Show me recent errors"
AI: ✅ Displays log content

AI maintains full context between your questions!

</td> <td width="33%" align="left">

🎯 Persistent Sessions

Natural Conversation Flow

You: "SSH to production server"
AI: ✅ Connected to prod-01
    Session: prod-01

You: "How much disk space left?"
AI: ✅ 45GB available
    (same session, no re-auth)

You: "Show me today's logs"
AI: ✅ Displaying logs...
    (same session continues)

You: "Restart the API service"
AI: ✅ Service restarted
    (still same session!)

The AI remembers everything:

  • ✅ Your SSH connections
  • ✅ Current directories
  • ✅ Environment variables
  • ✅ All previous context

</td> <td width="33%" align="left">

📁 Seamless File Transfer

Just Ask in Natural Language

You: "Upload my config to the server"

AI: ✅ Uploaded config.json
    /app/config/config.json

---

You: "Download the error logs"

AI: ✅ Downloaded app.log
    Saved to ./logs/app.log

---

You: "Get database backup"

AI: ✅ Downloaded backup.sql
    (even through SSH jumps!)

It just works:

  • ✅ Through any SSH session
  • ✅ Multiple jump hosts
  • ✅ Up to 10MB files
  • ✅ Binary and text files

</td> </tr> </table>


🎬 Real-World Example

Watch how a natural conversation becomes automated operations:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

👤 YOU ASK:
   "Debug the slow API on prod-server-01"

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

🤖 AI EXECUTES:

   [Connecting...]
   → ssh user@prod-server-01
   ✅ Connected to prod-server-01

   [Investigating processes...]
   → ps aux | grep api
   📊 API process found: PID 1234, using 98% CPU

   [Checking logs...]
   → cd /var/log/api && tail -n 100 error.log
   🔍 ERROR: Memory leak in /api/v1/users endpoint

   [Downloading for analysis...]
   → Download: /var/log/api/error.log → ./local-debug/
   ✅ Downloaded 2.4MB (analyzed: 500+ memory errors)

   [Applying fix...]
   → Upload: ./fixed-config.yml → /app/config/
   ✅ Uploaded new rate-limiting config

   [Restarting service...]
   → systemctl restart api-service
   → systemctl status api-service
   ✅ Service restarted, CPU now at 12%

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

🤖 AI RESPONDS:
   "Fixed! The API had a memory leak in the users endpoint.

   • Downloaded logs and found 500+ memory allocation errors
   • Applied rate-limiting configuration
   • Restarted service - CPU dropped from 98% to 12%
   • All operations completed in one persistent session"

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

✨ All in ONE session, NO re-authentication needed! ✨

📦 Installation

npm install -g mcp-shellkeeper

Configuration

<table> <tr> <td width="33%">

Cursor

Settings JSON:

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

(Cmd+Shift+P → Preferences: Open Settings)

</td> <td width="33%">

Claude Code

Config file:

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

(~/.config/claude/config.json)

</td> <td width="33%">

VS Code (Cline)

Settings JSON:

{
  "cline.mcpServers": {
    "shellkeeper": {
      "command": "npx",
      "args": ["-y", "mcp-shellkeeper"]
    }
  }
}

</td> </tr> </table>

Restart your AI assistant and you're ready! 🎉


💡 Use Cases

Scenario What You Ask What AI Does
🔍 Debug Production "Why is prod-api slow?" SSH → Check CPU/memory → Download logs → Analyze → Upload fix → Restart
🚀 Deploy Updates "Deploy v2.0 to staging" SSH → Backup → Upload files → Migrate DB → Restart → Verify
🔧 Update Configs "Update SSL certs on web servers" SSH → Download old certs → Upload new → Test → Reload nginx
🗄️ Backup Database "Backup prod DB to local" SSH through bastion → Dump DB → Compress → Download → Verify
📊 Analyze Logs "Find all 500 errors today" SSH → Parse logs → Download → Analyze locally → Report patterns
🔄 Batch Operations "Update configs on all servers" Parallel sessions → Upload → Restart → Download results

All through natural conversation with your AI! No scripts, no manual SSH juggling.


📖 Available Tools

The AI uses these tools automatically, but you can reference them for advanced use:

Tool Purpose Key Features
terminal_execute Run commands in persistent session Timeout config, exit code capture, clean output
terminal_upload_file Upload local → remote (max 10MB) Auto-detect directory, handle duplicates, works through SSH
terminal_download_file Download remote → local (max 10MB) Auto-create dirs, preserve permissions, verify integrity
terminal_new_session Create isolated session Parallel operations, separate environments
terminal_list_sessions View all active sessions Status, uptime, last command
terminal_close_session Clean up session Free resources when done
terminal_get_buffer Debug raw output Useful for troubleshooting

💡 Tip: The AI handles these automatically based on your natural language requests!


🔒 Security Best Practices

✅ DO:

  • Use SSH key authentication (not passwords): ssh-keygen -t ed25519
  • Jump through bastion hosts for production: ssh -J bastion.com user@prod
  • Limit file upload destinations (avoid /etc, /root, .ssh/)
  • Use read-only accounts for investigation
  • Clean up sessions after tasks
  • Audit all AI operations

❌ DON'T:

  • Store passwords in commands or configs
  • Upload untrusted files to production
  • Download sensitive data without encryption
  • Run destructive commands without verification
  • Grant unnecessary permissions

🛠️ How It Works

Persistent Sessions:

  • Uses PTY (Pseudo-Terminal) for full TTY emulation with state persistence
  • Smart markers detect command completion automatically
  • Exit codes captured for error detection
  • Output parsed clean (no ANSI codes)

File Transfer:

  • Base64 encoding through existing SSH sessions (no separate SCP/SFTP)
  • Works through jump hosts without re-authentication
  • Max 10MB, 5-minute timeout (completes early if faster)

🐛 Troubleshooting

<details> <summary><b>Commands timeout or hang</b></summary>

// Increase timeout for long-running commands
terminal_execute({
  command: "npm install",
  timeout: 120000  // 2 minutes
})

// Check if SSH keys are set up correctly
ssh -v user@server

</details>

<details> <summary><b>SSH asks for password</b></summary>

# Set up passwordless authentication
ssh-keygen -t ed25519
ssh-copy-id user@server

# Verify
ssh user@server "echo Success"

</details>

<details> <summary><b>File upload fails</b></summary>

// Check if in SSH session first
terminal_execute({ command: "pwd" })  // Verify you're on remote server

// Ensure remote directory exists
terminal_execute({ command: "mkdir -p /app/uploads" })

// Then upload
terminal_upload({ local_path: "file.txt", remote_path: "/app/uploads/file.txt" })

</details>

<details> <summary><b>File download fails</b></summary>

// Verify remote file exists
terminal_execute({ command: "ls -lh /path/to/file" })

// Check permissions
terminal_execute({ command: "cat /path/to/file | wc -l" })

// Try download with absolute path
terminal_download({ remote_path: "/full/path/to/file", local_path: "./" })

</details>

<details> <summary><b>Session becomes unresponsive</b></summary>

// List all sessions
terminal_list_sessions()

// Close problematic session
terminal_close_session({ session_id: "stuck-session" })

// Create fresh session
terminal_new_session({ session_id: "new-session" })

</details>


🧪 Development

# Clone repository
git clone https://github.com/tranhuucanh/mcp-shellkeeper.git
cd mcp-shellkeeper

# Install dependencies
npm install

# Build
npm run build

# Test locally with stdio transport
node dist/index.js

# Test with MCP Inspector
npm run inspector

🤝 Contributing

Contributions welcome! Help make AI-assisted server management better.

  1. Fork the repository
  2. Create feature branch (git checkout -b feature/amazing-feature)
  3. Commit changes (git commit -m 'Add amazing feature')
  4. Push to branch (git push origin feature/amazing-feature)
  5. Open Pull Request

📄 License

MIT License - see LICENSE file for details.

You can:

  • ✅ Use commercially
  • ✅ Modify
  • ✅ Distribute
  • ✅ Private use

🙏 Acknowledgments


📞 Support


<div align="center">

Built with ❤️ for the AI developer community

Stateful execution + File transfer = Limitless possibilities

Star History Chart

⬆ Back to top

</div>

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured