🖥️ Shell MCP Server

Created By
MCP-Mirrora year ago
Mirror of
Overview

What is Shell MCP Server?

Shell MCP Server is a tool that adds secure shell command execution capabilities to AI applications, specifically designed for the Model Context Protocol.

How to use Shell MCP Server?

To use Shell MCP Server, install it via pip and configure it in your AI application to enable shell command execution.

Key features of Shell MCP Server?

  • 🔒 Secure Execution: Commands run only in specified directories.
  • 🐚 Multiple Shells: Supports bash, sh, cmd, and powershell.
  • ⏱️ Timeout Control: Automatically terminates long-running commands.
  • 🌍 Cross-Platform: Works on both Unix and Windows systems.
  • 🛡️ Safe by Default: Built-in directory and shell validation.

Use cases of Shell MCP Server?

  1. Executing system commands securely in AI applications.
  2. Managing files and directories through shell commands.
  3. Performing project management tasks like Git operations.
  4. Monitoring system resources and processes.

FAQ from Shell MCP Server?

  • Can I use Shell MCP Server on Windows?

Yes! Shell MCP Server is designed to work on both Unix and Windows systems.

  • How do I install Shell MCP Server?

You can install it using pip with the command: pip install shell-mcp-server.

  • What security features does Shell MCP Server provide?

It includes directory isolation, shell control, timeout protection, and path validation to prevent traversal attacks.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
MCP-Mirror
Star
-
Language
-
License
-

Recommend Servers

View All
AI Work Market — USDC settlement rails for AI labor on Base Mainnet)
@Dario (DME)

AI Work Market is a USDC escrow protocol on Base Mainnet, designed for autonomous AI agents to find work, post jobs, and settle payments without humans in the loop. This MCP server exposes 10 tools: **Escrow lifecycle** - `create_intent_quote` — get calldata + gas estimate for funding a new escrow intent - `submit_proof_quote` — get calldata for the seller to submit a proof URI - `release_funds_quote` — get calldata for the buyer to release payment (or claim/refund) **x402 single-call binding** - `x402_consume` — replaces the 5-step x402 flow with one HMAC-signed POST that returns a delivery URL **Onboarding & discovery** - `agent_onboard` — generate a signed agent card with marketplace attestation - `agent_search` — tf-idf search over the live agent catalog - `agent_reputation` — server-side reputation from on-chain Released/Refunded/Disputed events **Live state** - `system_status` — live on-chain state (nextIntentId, accumulatedFees, contract balance, owner) - `escrow_rules` — contract semantics, lifecycle, call guides, failure modes - `events_subscribe` — SSE stream of new on-chain intent events All endpoints are serverless (Vercel) and return their schema on GET. No browser, no wallet UI required for an agent to integrate. The protocol takes a 1% commission on every settlement; the rest goes to the seller. The full AgentCard is at `/.well-known/agent-card.json` (A2A-compatible). The OpenAPI 3.0.3 spec is at `/.well-known/openapi.json` with `components.securitySchemes` (none, hmacX402). `robots.txt` allows GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended, CCBot, Amazonbot.

7 hours ago
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago