Cloudera AI MCP MCP Server

# Cloudera ML Model Control Protocol (MCP) This MCP implements a Python-based integration with Cloudera Machine Learning, allowing Claude to interact

Local serverstdioPython

What is the Cloudera AI MCP MCP server?

Cloudera AI MCP MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. # Cloudera ML Model Control Protocol (MCP) This MCP implements a Python-based integration with Cloudera Machine Learning, allowing Claude to interact with CML services programmatically. ## Features 1. Upload Folders: Upload entire.

Configuration and credentials

You will need 4 environment variables: CLOUDERA_ML_HOST, CLOUDERA_ML_API_KEY, CLOUDERA_ML_PROJECT_ID, PROJECT_ID. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

  • Python 3.8+ - requests - pathlib - python-dotenv - mcp[cli]

Setting it up

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.

Choosing this one

Among the developer tooling 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 adfr; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the cloudera ai mcp mcp server does with a few real requests.

How to install the Cloudera AI MCP MCP server

{
  "mcpServers": {
    "cloudera-ml-mcp-server": {
      "command": "python",
      "args": [
        "/path/to/MCP_cloudera/server.py"
      ],
      "env": {
        "CLOUDERA_ML_HOST": "https://ml-xxxx.cloudera.site",
        "CLOUDERA_ML_API_KEY": "your-api-key"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python 3.8+ - requests - pathlib - python-dotenv - mcp[cli]
VariableDescriptionRequired
CLOUDERA_ML_HOSTEndpoint or connection string the server talks to.Optional
CLOUDERA_ML_API_KEYCredential the server authenticates with.Yes
CLOUDERA_ML_PROJECT_IDConfiguration value read at startup.Optional
PROJECT_IDConfiguration value read at startup.Optional

Frequently asked questions

Python 3.8+ and the `requests`, `pathlib`, `python-dotenv`, and `mcp[cli]` packages.