"Information about file systems" matching MCP servers:

An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

Enables MCP clients to connect to SAP S/4HANA on-premise systems, providing developer-grade read and write access to ABAP source, DDIC objects, table data, syntax/ATC checks, debugging, and transport management.

A local Model Context Protocol server that allows LLMs to securely execute shell commands on remote Linux and Windows systems via SSH connections.

Provides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.

A comprehensive learning project demonstrating MCP server implementation with tools for calculator operations, file management, and system information retrieval, including Google ADK integration patterns and best practices.

Enables full ABAP development workflows against SAP systems via the ADT API, including reading and editing objects, running code, managing transports, executing tests, and performing code analysis.

A lightweight MCP server that enables AI agents to perform deep codebase analysis by leveraging Gemini's massive context window for cross-file analysis and intelligent file selection.

A Model Context Protocol server that enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

A minimal integration layer exposing PyTorch Lightning via a structured, machine-readable API for tools, agents, and orchestration systems.

Enables easy gRPC requests and Protocol Buffer file information retrieval through natural language commands. Supports unary RPCs with SSL, timeout configuration, and response time statistics.

Enables any MCP-compatible AI agent to directly operate PixInsight through about 80 tools for opening and editing images, running processes, PixelMath, astrometry, and channel operations.

Enables running multiple Claude prompts simultaneously in parallel with support for file contexts and output redirection to individual files.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.

Provides comprehensive documentation about AWS AgentCore framework to GenAI tools, enabling users to build production-ready AI agents with enterprise-grade security, observability, and scalability. Offers guidance on identity management, API integration, monitoring, code execution, memory storage, and tool integration for AI agents.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools like calculator and greeting functions, plus system information resources.

A Model Context Protocol (MCP) server for integrating Google's Gemini 3 models with Claude Code, enabling powerful collaboration between both AI systems.

A production-ready MCP server for coding workflows on Replit, enabling file management, sandboxed code execution, Git operations, and package management via natural language.

Enables AI assistants to create isolated Kubernetes Pod sessions for real-time shell command execution, file management, and Node.js code execution, with automatic TTL-based cleanup.

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.