"Retrieving information from document directory with search and memory capabilities" 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 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

An MCP (Multi-Agent Conversation Protocol) server that enables interaction with Google's Managed Service for Microsoft Active Directory through its OpenAPI, allowing users to manage identity resources through natural language.

MCP server for memory management with process inspection and cleanup tools.

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.

Enables a Claude Code cloud session to run shell commands inside a chroot jail on your own computer and to call the MCP servers already installed there, with every request authenticated and relayed over a Cloudflare quick tunnel so no router port is opened and no SSH key or tunnel is ever handed to the cloud VM.

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 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 clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

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.

Extends Claude Desktop with custom tools for file management, system operations, and command execution. Supports creating/reading/deleting files, directory listing, system information retrieval, and file searching capabilities.

Enables LLMs to interact with remote servers via SSH, supporting command execution, file upload/download, and directory listing.

Enables any MCP client to execute DeepSeek Harness agents and shell commands through standard MCP tools, bridging multi-agent capabilities with sandboxed execution.

Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.

Security-hardened MCP server that runs only allowlisted commands with no shell, jailed to a single directory, and bounded execution.

Provides comprehensive PC control capabilities including file operations (read, write, edit, delete), directory management, file search, and shell command execution through the Model Context Protocol.

Provides local agent capabilities for LM Studio including file I/O, terminal execution, and web search.

A collection of Model Context Protocol servers that enable Claude Desktop to provide development assistance capabilities with filesystem, Git, shell command, and web search functionality without incurring API usage costs.

Enables reading diagnostic data from remote servers over SSH using a whitelist of read-only commands, with secret redaction.

An MCP server that enables coding agents to execute and manage long-running shell commands asynchronously with capabilities for process monitoring, interaction, and lifecycle management.

Enables AI assistants to manage remote servers via SSH with 43 specialized tools for command execution, file editing, directory operations, and background tasks across Linux, macOS, and Windows.

Enables secure SSH connections to multiple remote servers with support for command execution, file transfers (SFTP), directory listing, and both password and key-based authentication.

Runs shell commands inside an existing microsandbox sandbox rather than on the Windows host, tracking the working directory and translating paths between the host project folder and the sandbox mount. Exposes tools for foreground or background execution with timeouts, output retrieval, killing processes, and listing them.

Enables execution of bash commands via MCP, allowing clients to run shell commands and set a working directory.

Enables interaction with remote MCP servers using SSE transport instead of STDIO for enhanced communication capabilities.

Enables AI agents to safely access and administer remote machines over SSH using existing OpenSSH config, with typed tools for running commands, reading and writing files, listing directories, and retrieving file metadata.

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.

Enables launching and controlling real, visible Windows Telnet windows by reading their screen buffers and sending keyboard events, with session management and text-waiting capabilities.

fork from https://github.com/JoshuaRileyDev/mac-apps-launcher