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Cloudera Hive MCP Server

by manojjain10

Cloudera Hive MCP Server

A standard Model Context Protocol server that exposes a Cloudera Data Warehouse Virtual Warehouse (Hive) to any MCP client — Claude Desktop, Claude Code, the Claude Agent SDK, LangChain, LlamaIndex, Cline, Continue, etc.

Tools

Tool

Purpose

list_databases

List every database in the Virtual Warehouse.

list_tables

List tables in a given database.

describe_table

Return columns, types, and comments for a table.

get_table_sample

Preview the first N rows (1–100) of a table.

execute_query

Run a HiveQL query. Read-only by default; row-capped for safety.

Related MCP server: Cloudera Iceberg MCP Server

Prerequisites

  • Python 3.10+

  • Network access to your Cloudera Virtual Warehouse (typically *.dw.cloudera.site:443)

  • A workload user + password with query privileges on the target VW

uvx is the Python analog of npx. It fetches the package, resolves its dependencies into an isolated cache, and runs the entry point — no clone, no venv, no pip install on the client machine.

One-time on the client machine — install uv (ships uvx):

curl -LsSf https://astral.sh/uv/install.sh | sh    # macOS / Linux
# Windows:  powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Then any MCP client can launch this server with:

uvx --from git+https://github.com/mjain/hive-mcp-server hive-mcp-server

(replace the Git URL with your fork / internal mirror)

Environment variables

The server needs Hive credentials in its environment. Every MCP client config below sets them via an env block — no .env file needed on the client.

Variable

Default

Description

HIVE_HOST

(required)

Virtual Warehouse hostname

HIVE_PORT

443

HTTPS port

HIVE_HTTP_PATH

/cliservice

HiveServer2 HTTP path

HIVE_USERNAME

(required)

Cloudera workload user

HIVE_PASSWORD

(required)

Cloudera workload password

HIVE_READ_ONLY

true

If true, execute_query rejects DDL/DML

HIVE_QUERY_ROW_LIMIT

1000

Max rows returned by execute_query

MCP_TRANSPORT

stdio

Transport passed to mcp.run(). Use stdio for MCP clients; set to sse when driving via the MCP Inspector.


Client setup

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "hive": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/mjain/hive-mcp-server",
        "hive-mcp-server"
      ],
      "env": {
        "HIVE_HOST": "your-vw-host.dw.cloudera.site",
        "HIVE_USERNAME": "your-workload-user",
        "HIVE_PASSWORD": "your-workload-password",
        "HIVE_READ_ONLY": "true"
      }
    }
  }
}

Fully quit Claude Desktop (⌘Q) and reopen. The five Hive tools appear in the tool tray.

Claude Code CLI

claude mcp add hive \
  --env HIVE_HOST=your-vw-host.dw.cloudera.site \
  --env HIVE_USERNAME=your-workload-user \
  --env HIVE_PASSWORD=your-workload-password \
  -- uvx --from git+https://github.com/mjain/hive-mcp-server hive-mcp-server

Add -s user before hive to make it available in every project.

Claude Agent SDK (Python)

# pip install claude-agent-sdk
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions

async def main():
    options = ClaudeAgentOptions(
        mcp_servers={
            "hive": {
                "type": "stdio",
                "command": "uvx",
                "args": [
                    "--from",
                    "git+https://github.com/mjain/hive-mcp-server",
                    "hive-mcp-server",
                ],
                "env": {
                    "HIVE_HOST": "your-vw-host.dw.cloudera.site",
                    "HIVE_USERNAME": "your-workload-user",
                    "HIVE_PASSWORD": "your-workload-password",
                    "HIVE_READ_ONLY": "true",
                },
            }
        },
        allowed_tools=[
            "mcp__hive__list_databases",
            "mcp__hive__list_tables",
            "mcp__hive__describe_table",
            "mcp__hive__get_table_sample",
            "mcp__hive__execute_query",
        ],
    )
    async for msg in query(
        prompt="List all Hive databases, then describe the largest table in the first one.",
        options=options,
    ):
        print(msg)

asyncio.run(main())

The same {command, args, env} shape works for LangChain's MCP adapter, LlamaIndex, Cline, Continue, Zed, and every other MCP client.


Local development

Clone and install in editable mode when working on the server itself:

git clone <this repo>
cd hive-mcp-server-claude
python -m venv .venv
source .venv/bin/activate
pip install -e .
cp .env.example .env    # fill in credentials
hive-mcp-server         # runs on stdio; Ctrl-C to stop

Smoke-test the connection:

python -c "from hive_mcp_server.tools.hive_tools import list_databases; print(list_databases())"

Code layout

The server follows the same pattern as cloudera/iceberg-mcp-server:

src/hive_mcp_server/
├── __init__.py           # version + main/mcp re-exports
├── server.py             # thin MCP registration layer (@mcp.tool wrappers)
└── tools/
    ├── __init__.py
    └── hive_tools.py     # config, connection, SQL safety, tool logic

To add a new tool: implement it in tools/hive_tools.py, then add a matching @mcp.tool() wrapper in server.py whose docstring becomes the tool description exposed to the LLM.

Transport

By default the server runs on stdio, which is what all MCP clients (Claude Desktop, Claude Code, etc.) expect. To use the MCP Inspector web UI instead:

MCP_TRANSPORT=sse hive-mcp-server

Publishing your own fork

Push to any Git host — clients reference the URL:

git init && git add . && git commit -m "initial"
git remote add origin https://github.com/<you>/hive-mcp-server
git push -u origin main

Then everyone points their uvx --from git+... at your URL. To publish to PyPI so clients can just say uvx hive-mcp-server (no --from):

pip install build twine
python -m build
twine upload dist/*

Safety

  • HIVE_READ_ONLY=true (default)execute_query rejects INSERT / UPDATE / DELETE / DROP / ALTER / TRUNCATE / CREATE / REPLACE / MERGE / GRANT / REVOKE / MSCK / LOAD / EXPORT / IMPORT.

  • HIVE_QUERY_ROW_LIMIT=1000 — caps execute_query results so a SELECT * on a billion-row table doesn't blow up the agent's context.

  • Identifier validationdatabase and table arguments must match [A-Za-z_][A-Za-z0-9_]*; anything else is rejected before reaching Hive.

  • No credentials in tool arguments — the connection is configured entirely through environment variables; agents cannot see or override them.

License

MIT.

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