"Dash" matching MCP servers:

MCP server that vets LLM-emitted shell commands BEFORE execution — detects rm -rf nested deep in chains, package-manager glob removal (apt remove 'nvidia'), dd/mkfs filesystem destruction, chmod 777 / chown -R privilege blast, network-exfil via curl | bash, chained shutdown/reboot, git destructive ops. 30 detection rules across 8 families. Sub-second, local, free, MCP-native.

Delegates coding tasks to the locally installed DeepSeek Harness CLI, enabling MCP clients to run prompts through dsh and receive results with exit code and timing.

Enables AI assistants to monitor and manage Linux infrastructure including services, logs, processes, disk, memory, ports, cron, nginx, Docker, and system health checks via the Model Context Protocol.

Sandboxed Bash for Agents. Full state capture on every command.

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

Sandboxed bash execution MCP server for AI agents, using an in-memory virtual filesystem overlay to prevent real filesystem damage, with configurable network access, timeouts, and optional Python/JS runtimes.

An MCP server that enables the execution of arbitrary bash commands and returns detailed output including stdout, stderr, and exit codes. It supports customizable working directories, execution timeouts, and environment variable configurations.

Enables executing shell commands without permission prompts, including running commands and managing background processes.

MCP server wrapping DeepSeek's agent harness tools into minimal/standard modes, enabling persistent shell, file editing, search, job management, and more via natural language.

Enables executing Bash commands, pipelines, and scripts across Windows, macOS, and Linux via MCP, with support for multiple runtimes, timeouts, working directories, and stream capture.

A cheap, fast execution layer for MCP agents that delegates file reads, edits, and command runs to a local DeepSeek Harness, reducing cost and latency while keeping the parent agent in control of planning and reasoning.

Exposes WSL bash as a structured tool to MiniMax Code, returning stdout, stderr, exit code, duration, and classification from a single call. Adds command safety classification, audit logging with rotation, concurrency limits, and binary discovery for agents running shell commands.

A framework for building Model Context Protocol (MCP) servers using pure Bash scripts, allowing for the creation of tools, resources, and prompts without Node.js or Python runtimes. It provides a complete implementation of the MCP spec compatible with any environment running Bash 3.2+ and jq.

Safety-gated SSH MCP server for DeepSeek Harness and standard MCP clients, enabling agents to use a laboratory server's GPU, runtime, and configured source workspace while keeping the server isolated from the public internet.

An MCP server for spawning and managing bash commands asynchronously. Run multiple shell commands in parallel and check their progress independently.

Enables executing bash commands with foreground/background support, timeouts, environment control, and OpenTelemetry observability.

Enables running shell commands on the local machine via MCP, using bash.

Enables Open WebUI to execute bash commands for coding tasks in a persistent projects workspace, with configurable timeouts and output limits.

MCP server that enables an AI agent to display rich Markdown content on a physical monitor connected to a headless Linux device via a Textual/Rich TUI.

Automates Spine asset pipeline tasks such as export, texture packing, resource validation, and file summarization through the Spine CLI.