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.
An MCP server that gives Claude structural understanding of a codebase—dependency graph, entry points, complexity ranking, and import cycles—without reading every file into context.
Provides tools for analyzing project structures, searching through codebases, managing dependencies, and performing file operations with advanced filtering capabilities.
Enables natural language code search across multiple local Git repositories, allowing users to register projects, search for code, and explore file structures through Claude.
A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.
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 local file management through natural language interactions using the Gemini API, with tools for listing, reading, writing, deleting, and updating files.
Enables LLM hosts like Claude Code or Codex CLI to inspect folder structures and read unstructured documents (PDF, PPTX, DOCX, SVG, and images) by returning raw text and images for the host to summarize or analyze.
A TypeScript-based server that visualizes project directory structures in Markdown format, automatically documenting file contents with syntax highlighting and supporting customizable exclusion patterns.
A local-only MCP server for understanding Git repositories, offering repository summary, recent changes, file hotspots, and hygiene checks without network access.
An MCP server that provides persistent memory for database schemas by storing table structures and metadata in a local SQLite file. It enables LLMs to save, retrieve, and manage database snapshots to maintain a structured understanding of database architectures.
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.
Enables AI assistants to incrementally build Laravel and Vue.js applications by creating file structures, methods, and code through natural conversation.