"file system" matching MCP servers:

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.

Query only the data you need from your JSON file and keep your context clean

Read-only MCP tools for coding agents to audit deployment targets, detect fabricated code, review backlog, database schema, analytics, ML models, architecture docs, and decision lenses.

Enables analysis of any GitHub repository to get architecture, file roles, execution flows, system design Q\&A, and structured agent context. Works with MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.

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 safe, concurrent file system operations with sandboxed directory access control, automatic encoding detection, optimistic locking, and precise code editing capabilities including search-replace and batch operations.

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

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.

Analyzes source code structure across multiple languages using tree-sitter, extracting classes, functions, methods, and metadata with precise line numbers for efficient codebase exploration and AI-assisted development.

Provides deep git file-level forensics tools to analyze detailed file histories, changes, and patterns within git repositories, focusing on individual file analysis rather than repository-wide operations.

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.

Provides file system tools, code analysis prompts, async tasks, and secure HTTP transport following the 2025-03-26 MCP specification.

A Model Context Protocol server that provides tools for mathematical calculations and directory listing, alongside prompt templates for code reviews and explanations. It enables file system access and resource reading through stdio transport.

Exposes type-aware code navigation and fast file search to AI agents via language servers, enabling definitions, references, symbols, and file lookup without reading entire codebases.

MCP server for fetching GitHub repository files and directory trees, supporting raw file content, unix-style directory trees, and enhanced trees with file sizes, depth limits, and filters.

Enables asking a consuming app in plain language to audit its design system usage, returning tables that sort every value and component by origin—design system, app-named, or none—along with token and contrast checks.

Provides AI-driven development tools including file system operations, multi-language code analysis with tree-sitter, Git operations, code execution, and system information retrieval.

Static codebase analysis as MCP tools — give AI coding agents a map of your repo instead of letting them burn half their tokens rediscovering it file by file.

An MCP server that exposes LSP-backed code navigation and editing tools to LLM agents using a single global config file to route file extensions to language servers.

Provides tools for AI-driven development workflows including file system operations, code analysis, code execution, web fetching, and search.