"Shell" matching MCP servers:

Takes a plain-language automation goal and returns a recommended tool stack, command, validation checks, recovery guidance, and a machine-readable package contract for agents and builders.

MCP server that lets Claude Code drive the local Codex CLI as a sub-agent for concurrent queries and optional file/shell actions, using the CLI's existing login and sessions.

MCP server that enables AI assistants to run multi-step agent pipelines (e.g., Issue Analyst → Code Writer → Test Runner → PR Opener) from conversations, with support for Devin, shell, Python, and HTTP agents.

Provides a workspace-safe, read-only bridge between browser-based AI planning/review and local coding agents, enabling structured plan, execution summary, and review handoffs without granting shell, file write, or Git push access.

A lightweight stdio-only MCP server that allows AI agents to run multiple tasks (e.g., Python code, HTTP requests, shell commands) in parallel or with dependencies, returning structured results in a single call.

Enables ChatGPT to supervise and control local Codex runtime sessions through a secure MCP interface, managing threads, turns, approvals, events, and recovery without exposing direct file, shell, Git, SSH, or model loop access.

A passive MCP server that exposes a toolbox of executable tools (shell, network, HTTP, AI search, SSH, S3 file operations) to autonomous agents via Streamable HTTP, with strong security features including Docker sandboxing and WAF.

Serves a local dsh workspace as a protected Streamable HTTP MCP endpoint, letting authenticated web AI agents read, search, patch, inspect, and operate the project, with optional shell commands, LSP support, and public tunneling.

MCP server that bridges Claude Code to Google Antigravity's CLI, enabling Claude to orchestrate Gemini workers in parallel for reading, writing, verifying, and autonomous tasks. It provides tools for single dispatch, parallel fan-out, background jobs, and handles permission, cwd, and shell pitfalls.

Runs isolated AI agents in Docker containers with persistent workspaces and conversation history. Each agent has access to file operations, shell commands, GitHub integration, and can connect to external MCP servers for additional tools.

Enables ESP32 XiaoZhi voice devices to command a Windows PC via MCP, including app control, file operations, screen vision, browser interaction, shell execution, and orchestration of local AI coding agents like Codex CLI and Claude Code.

Give AI agents Zero-Trust access to production infrastructure without the risks of granting them shell access. Actions are bounded by policy and an on-host runner.

A self-extending MCP server that enables AI agents to browse the web, execute shell and Node snippets, automate browser workflows, access files and git, communicate with other agents, and use dozens of domain-specific calculation and research tools.

An MCP server that enables AI agents to execute real-world actions through 10 specialized engines covering authenticated API calls, browser automation, visual QA, shell commands, file operations, job scraping, and parallel task execution.

jobd is a self-hostable, GPU-aware job broker that queues and routes shell commands across your own machines — picking workers by available VRAM and tool tags, streaming logs back, and surviving across sessions. It ships native MCP integration, so agents can submit, monitor, and control long-running or GPU jobs as tools.

MCP server for local-first agent handoff: enables AI sessions to publish curated context, list/read updates, route handoffs to specialists, and advance per-consumer cursors, with SQLite persistence and no shell or network access.

Agentic cloud platform with 45+ MCP tools. Deploy any containerized stack, debug live pods (shell, file editing, DB queries), manage custom domains & TLS, push to built-in container registry, scale pods, and manage GPU workloads. The infrastructure layer where AI agents ship software to production.

This MCP server bridges Claude Code with the Antigravity CLI (agy), allowing Claude to delegate tasks to Google Gemini models via configurable difficulty tiers. It verifies the actual backend model for every call, provides separate tools for safe ask/research vs. shell exec, and supports long-running background jobs.