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faizbawa/mcp-remote-ssh

faizbawa/mcp-remote-ssh

SSH access with persist
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Config template (adjust for your client)
claude mcp add mcp-remote-ssh -- npx -y mcp-remote-ssh
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
12 ★ · faizbawa/mcp-remote-ssh · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 12 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository faizbawa/mcp-remote-ssh;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals

mcp-remote-ssh

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

MCP server giving AI agents full SSH access -- persistent sessions, structured command output, SFTP file transfer, port forwarding, session transcript recording, and **secret-safe environment variable injection with automatic output redaction**.
Why this exists
Every other SSH MCP server is missing something: no password auth, no persistent sessions, no SFTP, no port forwarding, or no structured exit codes. This one has all of them -- plus the only MCP-level secret management that prevents AI agents from ever seeing your credentials.
Secret-Safe Environment Variables
**The problem:** When an AI agent needs to use API tokens, passwords, or keys on a remote server, the standard approach exposes secrets in the LLM's context window. The agent either reads the secret file (now it's in the conversation) or runs echo $TOKEN and sees the value in the output.
**The solution:** ssh_load_env_file reads secrets from a local file on your machine, injects them into the remote SSH session, and registers them for **automatic output redaction**. The AI agent can use the variables freely -- every tool response is scrubbed before it reaches the LLM.
How it works
1. **Local file read** -- the env file lives on your machine, never on the remote host
2. **Shell injection via builtins** -- uses read -r VAR remote) |
| ssh_list_forwards | List active tunnels |
| ssh_close_forward | Close a tunnel |
Quick start
Design
Built on **Paramiko** (SSH) + **FastMCP** (MCP protocol).
- ssh_execute uses exec_command() for clean structured output with real exit codes
- When secrets are loaded, ssh_execute feeds exports via stdin to a bash wrapper, then execs the actual command -- secrets never appear in the process tree
- ssh_shell_* uses invoke_shell() for persistent interactive sessions
- All blocking Paramiko calls run in run_in_executor to stay async
- Shell keeps a 500KB rolling buffer for shell_read` polling
Source
awesome · https://github.com/faizbawa/mcp-remote-ssh
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