"A tool for generating draw.io flowcharts from codebase analysis" matching MCP servers:

Zero-config MCP server that connects local codebases to AI assistants, providing secure project tree, regex search, file reading, and tech stack tools locally.

Provides secure and efficient tools for codebase analysis, including file management, metadata retrieval, and dependency tree traversal. It allows LLMs to explore project structures and search for configuration files within a restricted root directory.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

Assists in Advanced Persistent Threat malware analysis by providing tools to securely download samples via jump servers using SSH and SCP. It enables automated retrieval of remote files through a multi-hop configuration for analysis workflows.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

An MCP server that exposes macOS Spotlight search as tools, wrapping mdfind and mdls to provide full-text and metadata file search across the system.

Enables local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.

Enables an agent to inspect an audio folder and report what is inside each file — duration, sample rate, channels, codec and bitrate — and to group byte-identical files, identical decoded audio stored in different containers, and near-duplicate candidates, with suggested keeps and explicit differences, all read-only.

Local MCP server enabling Codex and ChatGPT to read/write files, execute commands, manage processes, use Git, and inspect images on the user's machine with full privileges.

A collection of small MCP servers for macOS automation that expose Apple Mail, MoneyMoney, and Spotlight functionality as tools via AppleScript and command-line, enabling AI applications to search mail, manage contacts and transactions, and perform system-wide file searches through natural language.

An MCP server that enables file system search and inspection, including directory listing, regex-based file name and content searches, and reading text, PDF, and DOCX files.

A secure, production-grade MCP server that provides filesystem operations, AST math evaluation, and system diagnostics for LLM agents.

A modular, extensible MCP multi-server hub that gives LLMs sandboxed file access, Git operations, web fetching, and persistent memory, deployable via Ansible.

A TypeScript prototype for an MCP-style registry providing local utility tools for shell command execution, filesystem access, and search functionality. It features Zod input validation and project manifest resource exposure for embedding into larger MCP implementations.

Enables forensic analysis of Windows notification databases (wpndatabase.db) from E01 forensic images, automatically extracting and parsing notification data with search, filtering, timeline analysis, and sensitive information detection capabilities.

A custom MCP server with 6 utility tools (file search, file reading, math calculation, JSON formatting, time query, system info) that demonstrates MCP protocol workflow and integrates with LangChain agents.

Enables intelligent analysis and organization of image collections with smart filename generation, metadata extraction, and automated folder organization. Supports batch processing, color analysis, EXIF data extraction, and multiple naming styles for efficient photo management.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.