"A tool for managing and working with file systems" matching MCP servers:

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

An MCP proxy that sits in front of any MCP server and exposes only the tools you actually use, ranked by usage across sessions with pins and hysteresis, while keeping every other tool reachable through one-hop search and direct calls. This keeps context small without losing access to the full upstream catalog.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

A Model Context Protocol server for secure, sandboxed file operations and project scaffolding with built-in search and regex capabilities. It is optimized for Windows environments and features configurable access controls to restrict operations to specific directories.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

A Model Context Protocol server providing file search and question tools for AI models. Enables keyword search in files with line numbers and integration with external chat services.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables AI agents to explore, analyze, and search file systems, with tools for directory trees, file statistics, duplicate detection, code counting, and multi-criteria file search.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

A powerful, security-hardened MCP server for intelligent file organization. Provides high-level atomic tools for organizing files into categories, detecting duplicates, extracting EXIF/ID3 metadata, scheduling automatic organization, and more — for use with Claude, Cursor, and Gemini CLI.

A powerful Model Context Protocol (MCP) tool for exploring and managing different types of databases including PostgreSQL, MySQL, and Firestore.

Provides agents with tools to score a page's AI readiness, check which AI crawlers robots.txt blocks, and assess passage citability—all performed locally.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

Turns any verb Registry into a real MCP server, where each verb becomes an MCP tool with its own Zod input/output schemas (zero drift).

Turns any OpenAPI spec into a single-tool MCP server where the model writes JavaScript against a typed api object in a QuickJS sandbox, so multi-step tasks run in one round trip and only the final result reaches context. Credentials, rate limiting, retries, write gating and audit logging stay on the host, outside the sandbox.

Enables AI-powered access to authoritative design systems knowledge, including W3C standards, WCAG guidelines, and best practices from 188+ curated entries via semantic vector search.

Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.

MCP proxy server with semantic tool search for LLM coding agents. It reduces context window usage by activating only relevant tools based on user queries.

Enables lightweight web search discovery and on-demand extraction of cleaned page text from supplied URLs, returning snippets, headings, links, and saved full text for longer pages.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

MCP server that gives Claude Desktop and other desktop MCP clients filesystem powers—read, write, edit, and manage files like AI coding assistants.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

Reduces Claude's context window costs by automatically summarizing inactive files to their public interfaces using AST parsing, keeping only the full contents of the currently active file.

Enables saving and managing files in a sandboxed local folder via MCP, with tools for listing, reading, writing, appending, searching, moving, and deleting files and directories.

An MCP server implementation of Anthropic's Think Tool prompt engineering technique that enables Claude to break down complex problems and enhance its reasoning capabilities by providing a simple tool that echoes back thoughts.

Enables comprehensive file operations including reading, writing, searching, and editing files with advanced features like regex-based replacements, line-specific modifications, and directory-wide search capabilities. Provides 8 robust tools for safe file manipulation with content verification and detailed error handling.

Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.