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HDFS MCP
Interact with Hadoop Distributed File System — list directory contents, read and write files, manage permissions, and inspect cluster health. Essential for big data and data engineering teams working with distributed storage at petabyte scale.
What is HDFS MCP?
HDFS MCP is a Model Context Protocol server published by apache that lets AI assistants interact with file systems services. Once configured, your assistant can call its connected tools in natural language instead of you hand-writing every request against the underlying API.
What Can You Do With It?
- Browse HDFS directories
- Read and write large files
- Inspect cluster health
How to Use This Server
- 1. Choose your AI clientAdd HDFS MCP to an MCP-compatible assistant (Claude, Cursor, VS Code, or any client listed in the official MCP docs).
- 2. Install the serverFollow the install instructions below. Most servers install with a package manager in a few minutes and need only an API key or a local credential.
- 3. Add it to your configurationWrite the server block into your client's config file exactly as the official docs publish — including any arguments, environment variables, and path fields.
- 4. Start askingRestart your client and describe the task in natural language — the assistant uses the server's tools against your real data and services.
Server Specs
- Publisher
- apache
- Category
- File Systems
- Difficulty
- Advanced
- Tags
- HDFSHadoopBig DataDistributed
Get It Set Up
Security note: MCP servers run with the credentials you give them. Only install servers you trust, review tool lists before enabling them, and use scoped credentials (read-only tokens where possible). Axonix is an independent directory, not the publisher of this server.