Synology MCP Server

The Synology MCP Server is a purpose‑built bridge that lets AI assistants such as Claude, Cursor, or the Xiaozhi web client interact directly with a Synology NAS. By exposing the NAS’s file system and download manager through the Model Context Protocol, developers can give conversational agents the ability to list, read, write, and delete files, as well as manage active downloads—all while maintaining the security guarantees of Synology’s authentication system. This solves a common pain point for teams that rely on AI to automate file‑centric workflows: without a dedicated server, assistants would need custom code or insecure workarounds to touch the NAS.

At its core, the server authenticates with the Synology API using a username and password supplied in an environment file. Once logged in, it establishes a session that the MCP client can reuse for subsequent requests. The server supports both standard stdio streams (for desktop agents) and WebSocket connections (for web‑based clients like Xiaozhi), thanks to a unified architecture that can run both protocols side by side. This flexibility means the same deployment can serve multiple assistants simultaneously, reducing operational overhead.

Key capabilities include:

• File operations: list directories, read text or binary files, create, move, and delete items.
• Download management: start new downloads, pause/resume existing ones, and query status.
• Session persistence: automatic re‑login on startup and optional SSL verification toggling.
• Multi‑client support: a single instance can handle both stdio and WebSocket clients, enabling hybrid workflows.

Real‑world scenarios that benefit from this server are plentiful. A developer can ask an AI assistant to “pull the latest build artifact from ”, or a support engineer might instruct an assistant to “pause all torrents while the network is down”. In continuous‑integration pipelines, a CI tool could trigger an AI agent to archive logs directly onto the NAS after a job completes. The ability to control downloads also opens up use cases like automated media ingestion or scheduled backups that the assistant can orchestrate without manual intervention.

Integrating the Synology MCP Server into an AI workflow is straightforward: add a server entry to the assistant’s configuration, point it at the Docker compose file or Python script, and provide the required Synology credentials. Once running, the assistant can issue MCP commands as if it were a local file system, with all operations performed on the NAS in real time. This seamless blend of AI and infrastructure makes the Synology MCP Server an invaluable tool for developers looking to extend conversational agents into the realm of file management and network‑level tasks.