HDFS MCP Server is a controller based on MCP (Model Context Protocol) that provides access to HDFS clusters through the MCP protocol. The server
HDFS MCP Server is a controller based on MCP (Model Context Protocol) that provides access to HDFS clusters through the MCP protocol. The server supports basic HDFS operations such as file upload, download, move, copy, and provides. The hdfs mcp mcp server wraps that behind the Model Context Protocol, so an assistant can use it rather than through you.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
You will need 2 environment variables: HDFS_NAMENODE, NAMENODE_PORT. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
uv package managerAmong the file and storage access options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by will-sh; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Hdfs MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
### MCP Configuration
```json
{
"mcpServers": {
"hdfs-controller": {
"command": "uv",
"args": [
"--directory",
"/path/to/your/hdfsmcp",
"run",
"hdfs.py"
],
"env": {
"HDFS_NAMENODE": "your_namenode_hostname",
"NAMENODE_PORT": "your_namenode_port"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
uv package manager| Variable | Description | Required |
|---|---|---|
| HDFS_NAMENODE | Configuration value read at startup. | Optional |
| NAMENODE_PORT | Configuration value read at startup. | Optional |
Scoped local file access — read, write, search and reorganise files in directories you explicitly allow.
Search and read your Drive — Docs, Sheets and files become context your assistant can actually use.
Query, modify and analyse local SQLite databases in conversation — the fastest way to chat with a data file.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Chat with your second brain — search, read and write vault notes through the Local REST API.
Connects AI models to an Obsidian knowledge base for direct access and manipulation of notes and folders.