Tusky MCP Server

Tusky MCP Server – Bridging AI Assistants with Tusky Storage

The Tusky MCP Server addresses a common pain point for developers building AI‑powered workflows: the need to access and manipulate data stored in a third‑party platform from within an AI assistant. By implementing the Model Context Protocol, it gives Claude and other MCP‑compatible assistants a clean, standardized interface to Tusky’s storage and Mastodon integration. This removes the burden of writing custom API wrappers for each AI client, allowing teams to focus on business logic rather than plumbing.

At its core, the server authenticates with Tusky using an API key and exposes a set of resources that mirror Tusky’s vault, folder, and file concepts. Developers can create, list, update, or delete vaults and folders, upload and download files, and even perform full‑text searches across all stored content. The inclusion of the TUS protocol for uploads guarantees reliable, resumable transfers even over flaky networks—a crucial feature when AI assistants handle large media files or data sets.

Key capabilities are presented as “tools” that MCP clients can invoke directly. Authentication is handled through a simple challenge, after which the assistant has seamless access to the user’s profile and storage settings. File management tools allow uploading, downloading, and metadata updates, while search tools enable quick retrieval of relevant documents or media. Because all operations are expressed through the MCP schema, developers can compose complex workflows—such as having an assistant summarize a document after uploading it to a specific vault—without writing additional glue code.

Real‑world use cases include content creators who need to store drafts in Tusky vaults while an AI assistant drafts or edits them, data scientists who upload datasets to Tusky and have Claude generate exploratory analyses, or customer support teams that retrieve user‑submitted files stored in Tusky to answer queries. In each scenario, the MCP server eliminates friction: the assistant can authenticate once and then perform all required operations as if they were local file system calls.

Integrating the server into an AI workflow is straightforward. Once the MCP client (Claude Desktop, Cursor, etc.) is configured to point at the server process, every tool becomes available as a command the assistant can invoke. The assistant’s prompt can request actions like “search for all files tagged ‘report’ in vault X” or “upload this PDF to folder Y,” and the server translates those requests into Tusky API calls, returning structured results. This tight coupling lets developers build conversational interfaces that feel native while leveraging Tusky’s robust storage and social features.