"A server to interact with an SQL database with insert operation support (LiteSQL, DuckDB, Postgres)" matching MCP servers:

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

Memory bank with Server as SSH support for central knowledge base

A TypeScript implementation of a Model Context Protocol server that enables language models to securely query PostgreSQL databases, including those behind SSH bastion tunnels.

Enables AI agents to securely connect to and manage remote servers via SSH, with tools for running commands, file operations, log inspection, service management, and system monitoring under configurable access controls and audit logging.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

A demo MCP server that enables users to interact with various tools through natural language, including note management, weather queries, calculations, file operations, and shell commands. Uses Ollama for intent detection and structured command parsing from free text input.

Enables AI agents to control and interact with a local Windows computer through authenticated MCP tools, including file operations, shell commands, process management, HTTP requests, and system/media inspection.

Enables remote server control via SSH through Claude, supporting command execution, file transfers, and multi-server management with both standard and streamable HTTP protocols.

Enables AI-assisted development tools like Cursor, Cline, and Windsurf to request user confirmation before acting, running shell commands and displaying their output inside a Qt feedback window that returns user notes and logs to the model. This human-in-the-loop loop lets the assistant consolidate many speculative tool calls into a single feedback-aware request, saving API usage and improving accuracy.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

A simple MCP server that exposes a terminal tool, allowing AI agents to execute shell commands.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

A local MCP runtime for macOS and Windows that enables ChatGPT to read, edit, search, run tests, and capture screenshots in your local project folder while keeping your source code on your machine.

SSH orchestration MCP server for coding agents, enabling persistent bash sessions, hash-protected remote file editing, SFTP transfers, SSH tunnels, and multi-host orchestration with connection reuse across tools.

A secure shell command execution server implementing the Model Context Protocol (MCP). This server allows remote execution of whitelisted shell commands with support for stdin input.

An enhanced Model Context Protocol filesystem server that fixes common limitations and adds features like glob pattern search, head/tail reading, intelligent file editing with syntax validation, and new tools for delete and command execution.

Enables AI assistants to manage remote servers via SSH with 14 commands for execution, file transfer, auditing, and monitoring.