My MCP SSH

Overview

my‑mcp‑ssh is an MCP server that bridges large language models to remote systems through the familiar SSH protocol. It allows AI assistants to open secure shell sessions, run arbitrary commands, and transfer files—all while keeping credentials hidden from the model itself. By exposing SSH as an MCP tool, developers can embed remote execution directly into conversational workflows, enabling the assistant to diagnose servers, deploy code, or fetch logs without manual intervention.

The server’s core value lies in its seamless integration with AI workflows. Once a model receives an MCP request, the server establishes an SSH connection using parameters supplied in the payload or defaults from environment variables. The model can then invoke tools such as , , , or to interact with the remote host. Because each tool is defined in MCP, the assistant can chain operations—e.g., connect to a server, run a status command, and upload a configuration file—all within the same conversation. This eliminates context switches between CLI tools and chat interfaces, making remote management feel natural to the user.

Key capabilities include:

• Connection Management: Persistent sessions with configurable timeouts, reducing the overhead of reconnecting for each task.
• Command Execution: Arbitrary shell commands with output size limits to keep responses concise and prevent token overflow.
• File Transfer: Secure upload/download of files, supporting large binaries while respecting the model’s token budget.
• Credential Handling: A hierarchical authentication scheme that prefers explicit parameters, falls back to a pattern‑matching credentials file, and finally to environment variables. The file is auto‑protected with permissions and excluded from source control, ensuring secrets never leak.

Real‑world scenarios where my‑mcp‑ssh shines include:

• Automated DevOps: A CI/CD pipeline that hands off deployment steps to a model, which then SSH‑es into staging servers, runs tests, and reports results.
• Remote Troubleshooting: Support agents asking a model to SSH into customer servers, execute diagnostics, and suggest fixes—all within the chat interface.
• Hybrid Cloud Management: Managing a fleet of servers across on‑prem, AWS, and Azure by simply changing the host parameters in the MCP request.

Because it adheres strictly to MCP’s declarative tool interface, developers can plug this server into any existing Claude or other LLM ecosystem with minimal friction. The result is a powerful, secure, and developer‑friendly way to extend AI assistants with true remote execution capabilities.