MCP server that enables LLMs to read and analyze Microsoft Project schedules, including critical path, resources, and advanced construction planning layers (AWP and LPS) for work packages and Lean planning.
A FastMCP server that exposes predefined artifacts as Resources and project lifecycle operations as Tools for creating, updating, deploying, debugging, testing, monitoring, and configuring projects with minimal token usage.
Enables rapid creation of new projects from predefined templates including React, Node.js, Django, Flask, and more. Provides comprehensive project scaffolding with file system operations, template management, and command execution capabilities.
An MCP server that provides access to project files and their contents, allowing users to retrieve file data from specified project directories with error handling and configuration options.
MCP server for pre-print QA of Bambu Studio projects, providing tools to inspect models and 3MF files, validate risky settings, create support variants, and open files in Bambu Studio.
MCP server that scans workspace roots to build a registry of version-controlled projects, exposing tools for searching, listing, and inspecting projects to help AI coding agents navigate multi-repo workspaces efficiently.
A personal MCP server for managing a folder of markdown notes. It provides tools to search and list notes, resources to access individual notes, and a prompt for weekly summaries.
An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.
Enables Claude Web to securely inspect, search, and modify local project files through a sandboxed MCP server with atomic writes, path traversal protection, and sensitive file blocking.
This MCP server integrates with Azure AI Foundry's Claude deployment to provide document management functionality. It enables tools for reading, writing, and listing files, allowing Claude to interact with local documents through an Azure-compatible client.
A tutorial MCP server for learning the Model Context Protocol by building file and system tools. Provides hands-on experience creating custom tools that enable AI models to interact with files and execute system commands.
Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.
A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.
Enables interaction with the WhkerDB shared PDF editor to manage collaborative rooms, file structures, and real-time annotations. It allows users to upload PDFs and images, manage note trees, and sync data across platforms through natural language.
Enables safe file system operations including reading, writing, updating, and deleting files with built-in security safeguards, automatic backups, and comprehensive error handling. Provides directory listing, file metadata extraction, and protects against operations on system-critical paths.