WebDAV MCP Server

Overview

The WebDAV MCP Server bridges the gap between AI assistants and WebDAV‑based file systems. By exposing a full set of CRUD (Create, Read, Update, Delete) operations as MCP resources and tools, it lets Claude Desktop or any MCP‑compatible client manipulate files on a remote WebDAV server using natural language commands. This eliminates the need for custom scripts or manual uploads, enabling developers to treat a WebDAV store as an integrated part of their AI workflow.

Why It Matters

Developers often need to retrieve, modify, or archive documents stored in legacy WebDAV repositories while working within an AI‑driven environment. Traditional approaches require separate authentication flows, REST APIs, or command‑line utilities—each adding friction and potential security gaps. The WebDAV MCP Server consolidates these steps: a single MCP endpoint handles authentication, connection pooling, and error handling. This streamlines the development cycle, reduces boilerplate code, and keeps file operations within the same conversational context that drives AI reasoning.

Core Capabilities

• Universal WebDAV Support – Connect to any compliant server, optionally with basic authentication. Plain‑text passwords are required for the WebDAV layer, while the MCP server itself can use bcrypt‑hashed credentials.
• Full CRUD Exposure – Files and directories are represented as resources; operations such as , , , and become first‑class tools in the MCP toolkit.
• Transport Flexibility – Run over stdio for tight integration with desktop clients, or expose an HTTP/SSE endpoint for remote access and real‑time updates.
• Performance Optimisation – Connection pooling minimizes latency when repeatedly accessing the same WebDAV server, a common pattern in AI workflows that iterate over many files.
• Robust Configuration – Environment variables, Zod validation, and structured logging provide a developer‑friendly setup that catches misconfigurations early.

Real‑World Use Cases

• Document Retrieval for Summaries – An AI assistant can fetch a PDF from a WebDAV archive, summarize its contents, and return the summary—all through natural language prompts.
• Automated Data Pipelines – A data scientist can instruct the assistant to move raw datasets into a staging folder, trigger preprocessing scripts, and then archive results back to WebDAV.
• Content Management – Writers or editors can use the assistant to upload drafts, rename files, and organize directories without leaving their chat interface.
• Backup & Versioning – Developers can script automated backups of code repositories or configuration files directly to a WebDAV storage, leveraging the assistant’s conversational control.

Integration with AI Workflows

Once deployed, any MCP client can register the server’s resources and tools. The assistant then treats file operations as natural language actions, generating tool calls that the MCP server executes behind the scenes. Because the server handles authentication and error reporting, developers can focus on higher‑level logic—such as conditional branching based on file existence or content analysis—without worrying about the underlying protocol details.

Standout Advantages

• Unified Authentication – Separate credentials for the WebDAV layer and the MCP server allow fine‑grained access control without compromising security.
• SSE Support – Real‑time event streams enable progress updates for long uploads or batch operations, improving user experience in interactive sessions.
• Zero Code Required – By exposing all functionality through MCP, developers avoid writing custom HTTP clients or WebDAV wrappers; the assistant handles everything conversationally.

In summary, the WebDAV MCP Server turns a traditional file store into an AI‑friendly resource hub. It simplifies complex file interactions, enhances security with optional bcrypt hashing, and integrates seamlessly into existing AI assistant workflows—making it an essential tool for developers who need to bridge legacy file systems and modern conversational AI.