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.
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.
Real-World Example • Installation • Core Features • Use Cases • Tools
</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.
- Fork the repository
- Create feature branch (
git checkout -b feature/amazing-feature) - Commit changes (
git commit -m 'Add amazing feature') - Push to branch (
git push origin feature/amazing-feature) - Open Pull Request
📄 License
MIT License - see LICENSE file for details.
You can:
- ✅ Use commercially
- ✅ Modify
- ✅ Distribute
- ✅ Private use
🙏 Acknowledgments
- Built with Model Context Protocol SDK
- Uses node-pty for terminal emulation
- Inspired by the need for stateful command execution in AI workflows
📞 Support
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- MCP Community: Discord
<div align="center">
Built with ❤️ for the AI developer community
Stateful execution + File transfer = Limitless possibilities
</div>
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.