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"How to run local command-line commands" matching MCP servers:

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    Provides tools for executing shell commands both synchronously and asynchronously with real-time output streaming and process management capabilities. It enables users to start background tasks, monitor progress, and manage long-running processes via Stdio or HTTP transports.
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    An MCP server for tracking and managing AI command usage history using a PostgreSQL database. It enables users to log, search, and view statistics for various AI-related commands and their execution contexts.
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    Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.
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    MIT
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    Enables execution of shell commands, directory navigation, and interactive program automation through an enhanced command-line interface. Provides tools for running commands, managing working directories, and handling interactive programs using expect/send sequences.
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    MIT
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    A proxy server that enables AI assistants to run and interact with command-line applications like Expo through the Model Context Protocol (MCP), capturing logs and allowing keypress forwarding.
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    MIT
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    A secure MCP server example that demonstrates how to deploy to Google Cloud Run with authentication and identity token protection. Serves as a tutorial template for building production-ready MCP servers in the cloud.
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    Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.
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    192
    MIT
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    An MCP server that provides session-based shell command execution and file management with intelligent LLM-powered summarization. It enables users to manage isolated workflows and track progress through automated event logging and session history.
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    A 100% local development monitoring tool that captures browser console logs, network requests, and backend server output for analysis by AI assistants via MCP. It enables LLMs to debug applications by providing structured, real-time access to full-stack log data and persistent local storage.
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    MIT
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    Allows executing shell commands within a secure Docker container through Claude's MCP interface, providing Kubernetes tools and isolated environment without host Docker daemon access.
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    • Apple
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    Exposes your project's package.json scripts as MCP tools, allowing AI assistants to discover and execute npm/yarn/pnpm/bun scripts directly. Automatically detects your package manager and enables running scripts with optional arguments through natural language commands.
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    Enables Notion AI to interact with local files, execute shell commands, and delegate complex tasks to local AI agents. Provides file operations, command execution, and task delegation capabilities for local workspace management.
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    Connects AI systems to Local Falcon API, enabling access to local SEO reporting tools including scan reports, trend analysis, keyword tracking, and competitor data through the Model Context Protocol.
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    Enables AI assistants to intelligently search and explore local file systems using native Unix commands (ripgrep, find, ls) with token-optimized output, automatic pagination, and multi-layer security validation.
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    A local MCP server that wraps the Obsidian CLI to give AI assistants direct access to read, edit, and manage notes within an Obsidian vault. It enables advanced operations such as frontmatter property management, context-aware searching, and the execution of internal Obsidian commands.
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    Integrates the LINE Messaging API with AI agents via the Model Context Protocol, supporting both stdio and SSE transport protocols. It allows agents to send messages, manage rich menus, and retrieve user profile information for LINE Official Accounts.
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    2,665
    Apache 2.0
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    Provides semantic code search capabilities that run 100% locally using EmbeddingGemma embeddings. Enables finding code by meaning across 15 file extensions and 9+ programming languages without API costs or sending code to the cloud.
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    A local Model Context Protocol server designed to share contextual information between an AI and a user. It primarily provides a tool to retrieve the current date and time in ISO 8601 format based on the server's local timezone.
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    A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.
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    • Apple
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    Enables AI assistants to search, read, create, and modify Markdown notes in local Obsidian vaults directly through filesystem operations. Supports tag-based discovery and frontmatter parsing without requiring Obsidian to be open, facilitating integration with VS Code Copilot via stdio transport.
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    A local-first MCP server for generating production-ready React UI components entirely offline without requiring API keys or configuration. It provides tools to search, list, and create over 30 types of components including buttons, forms, and layout elements.
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    Converts VSCode into an MCP server that enables external clients to remotely execute VSCode internal commands, query workspace information, and interact with the editor through HTTP streaming. Built on the FastMCP framework with security controls and real-time monitoring.
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    A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.
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    MIT
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    Provides Claude Desktop with direct access to your local file system for development tasks, enabling file operations (read, write, edit), directory browsing, command execution, and codebase search within a configured projects directory.
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    Provides web scraping, crawling, and site mapping capabilities by connecting directly to a self-hosted Firecrawl instance. It enables users to extract website content in markdown format and manage crawling jobs without an external API key.
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    A minimal FastMCP server implementation that provides basic mathematical and greeting tools. Enables users to perform simple operations like adding numbers and greeting people by name through a lightweight MCP interface.
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    MIT
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    Enables monitoring and analysis of local application log files with real-time tailing, error tracking, and search capabilities. Perfect for debugging Node.js applications, web servers, or any application that writes to log files through natural language commands.
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    Provides 18 tools including calculator operations (add, subtract, multiply, divide, power, sqrt, log, trigonometric functions) and secure sandboxed file operations (read, write, append, delete, list) for LangGraph agents and MCP clients. Features async support, YAML configuration, comprehensive logging, and path traversal protection.
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    Enables AI assistants to access and interact with Cursor/VS Code Local History data for file recovery and enhanced context awareness. Provides tools to browse file history, search across snapshots, and restore previous versions of files.
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    Provides persistent local memory functionality for AI assistants, enabling them to store, retrieve, and search contextual information across conversations with SQLite-based full-text search. All data stays private on your machine while dramatically improving context retention and personalized assistance.
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