Box MCP Server

The Box MCP Server bridges Claude‑style AI assistants with the Box cloud platform, enabling seamless interaction with files, folders, and collaboration features directly from natural language prompts. By exposing Box’s REST API through a Model Context Protocol interface, the server allows AI agents to perform complex document workflows—such as querying metadata, generating reports from templates, or managing shared links—without writing code. This solves a common pain point for developers: integrating secure, authenticated access to enterprise file storage into conversational AI pipelines.

At its core, the server implements a set of tool collections that mirror Box’s own capabilities. Each tool encapsulates a specific domain—file operations, folder management, collaboration controls, metadata handling, and search—and presents it as a callable action to the AI. For example, an assistant can ask “Show me all PDFs in the Marketing folder” and the server will translate that into a Box search query, returning the results in a structured format. The tools are designed to be AI‑friendly: they accept natural language parameters, perform validation against Box’s API schema, and return concise responses that the model can use to continue the conversation or generate new actions.

Key features include:

• Authentication flexibility: Supports both OAuth2.0 and CCG (client‑credential grant) flows, allowing deployment in single‑user or enterprise contexts. The server also offers a toggle to disable authentication for local testing.
• Transport options: Operates over stdio, Server‑Sent Events (SSE), or streamable HTTP, giving developers control over latency and scalability.
• Rich toolset: From basic file read/write to advanced document generation () and group management, the server covers almost every use case a content‑centric organization might need.
• Extensibility: The modular design lets teams add new Box API endpoints or custom logic without altering the core server, making it future‑proof as Box evolves.

Typical use cases span multiple industries:

• Content production: Writers and editors can ask the AI to fetch the latest version of a draft, merge metadata tags, or generate summary PDFs on demand.
• Compliance & governance: Legal teams can query for documents with specific compliance tags, audit access logs, or automatically archive outdated files.
• Collaboration automation: Project managers can create shared links, invite collaborators, or update folder permissions through conversational commands.
• Data science workflows: Analysts can pull datasets from Box, run transformations via AI‑generated scripts, and store results back into the cloud.

Integrating the Box MCP Server into an AI workflow is straightforward: a Claude or similar model receives a user prompt, selects the appropriate tool, and invokes it through the MCP interface. The server authenticates with Box, performs the requested operation, and streams the result back to the model. The assistant can then respond contextually or trigger additional actions, creating a fluid loop of natural language interaction and cloud operations. This tight coupling eliminates the need for manual API calls, reduces friction for non‑technical users, and accelerates delivery of AI‑powered document solutions.