File Systems

An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.

A FastAPI-based server that provides tools for local file management and Databricks operations, enabling users to create/edit files locally and interact with Databricks clusters, jobs, and DLT pipelines.

Enables AI assistants to search and access arXiv papers through a Model Context Protocol interface, allowing for paper search, download, listing, and reading functionality.

An MCP server that enables AI assistants to load, query, and analyze local CSV files using tools for filtering, aggregation, and grouping. It provides capabilities to describe schemas, calculate statistics, and sample data directly from CSV files.

Enables AI assistants to interact with LinkedIn and LinkedIn Sales Navigator for searching profiles, managing leads, and handling messaging via cookie-based authentication. It supports professional networking tasks such as sending connection requests and retrieving account details through the Model Context Protocol.

Enables extraction of design context from Figma files as CSS-like properties and provides tools to render Figma nodes as images. It integrates with AI agents via the Model Context Protocol to facilitate design-to-code workflows by providing layout, style, and typography information.

Enables searching and downloading audio samples from Freesound using keywords, filters, and sound IDs. It provides detailed sound metadata including duration, license information, and preview URLs.

CUFinder MCP Server provides AI assistants with direct access to 1B+ professional profiles and 85M+ company records for real-time B2B lead generation, contact discovery, and data enrichment.

Enables LLMs to read and extract content from PDF files with high-fidelity LaTeX recognition and layout awareness using a Python-based extraction engine. It includes a robust Node.js fallback and supports page range filtering for efficient processing of large documents.

A proof-of-concept MCP server that enables reading local files and performing basic arithmetic operations. It provides a simple foundation for understanding how tools are exposed to MCP clients.

An AI-powered server for code analysis, requirements validation, and automated fix proposals with human-in-the-loop confirmation. It supports multiple LLM providers and ensures safe file modifications through automatic backups and path validation.

Provides persistent agent workspaces with MongoDB storage for file management and real-time task progress tracking. It enables secure, isolated user environments with full activity logging for workspace operations.

MCP server for Microsoft Exchange / OWA — email, calendar, directory, availability

Lightweight persistent memory for AI agents. Hybrid search. 16 tools. One SQLite file.

Enables AI to upload local files to RustFS storage service and download files from HTTP/HTTPS URLs to local paths. Built with FastMCP and RustFS SDK for seamless file operations through natural language.

A demonstration project that uses Google Gemini 2.0 Flash to interact with a locally hosted Model Calling Protocol server for managing user registration data stored in CSV files.

A Model Context Protocol server that enables interaction with Hadoop Distributed File System, allowing operations like listing, reading, writing, and managing HDFS files and directories.

A model-agnostic Model Context Protocol server implementation that works with any compatible AI model or client, allowing tools like file operations to be accessed through the MCP standard.

Manages knowledge graph data synchronized with GitHub repositories, enabling remote storage and collaboration of memory entities, relationships, and observations.

Query professional profiles, search candidates, and get AI-powered summaries and job fit analysis.

A comprehensive Model Context Protocol server providing capabilities for web scraping, data analysis, system monitoring, file operations, API integrations, and report generation.

Enables interaction with Google Sheets, Docs, and Drive to manage spreadsheets, documents, and files. It supports operations like reading and updating cell data, extracting text from documents, and searching or sharing files within Google Drive.

A macOS-based MCP server that enables high-accuracy text extraction from PDF and image files using the OwlOCR app or Apple's Vision Framework. It supports multi-language OCR and provides asynchronous tools for processing documents directly within MCP clients.

Provides token-efficient semantic search and document retrieval by indexing PDFs, text, and markdown files into local notebooks using ChromaDB. It enables AI agents to query relevant passages from large documents through local embedding models like Hugging Face or Ollama.

An MCP server that exposes Autodesk Platform Services (APS) as tools for AI assistants to interact with the APS Data Management API. It enables users to authenticate and manage hubs, projects, and folders through a standardized interface.

A comprehensive bridge connecting AI agents to Unreal Engine 5.7 through 39 MCP tools for scene manipulation, asset management, and blueprint control. It enables real-time perception and editor automation using the Remote Control API and file-based protocols.

Processes test scenarios from user prompts to generate complete WDIO test suites with intelligent file management that analyzes existing files to determine whether to update them or create new ones.

A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.

A Model Context Protocol server built with FastMCP that features dynamic tool loading and modular management via a dedicated tool directory. It supports both stdio and HTTP transport modes, enabling efficient development and deployment of custom MCP tools.

An advanced Model Context Protocol server that integrates real-time weather data, local file system navigation, and geographic information with AI-powered analysis tools. It enables users to perform complex data evaluations and manage files while accessing live climatic and demographic data through compatible MCP clients.