Skip to main content
Glama
SpanishST

Hue MCP Server

by SpanishST
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
HUE_HOSTYesHue server URL (e.g., https://hue.example.com)
HUE_PASSWORDYesPassword for Hue authentication
HUE_USERNAMEYesUsername for Hue authentication
HUE_VERIFY_SSLNoVerify SSL certificates (default: true)true
HUE_SSL_WARNINGSNoShow SSL warnings (default: false)false

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
hue_execute_queryA

Execute a SQL query on Hue and return the results.

This tool executes a SQL statement, waits for completion, and fetches all results.
Use this for SELECT queries where you want to retrieve data.

Args:
    statement: The SQL statement to execute (e.g., "SELECT * FROM table LIMIT 100")
    dialect: SQL dialect to use - 'hive', 'sparksql', or 'impala' (default: 'hive')
    timeout: Maximum time to wait for query completion in seconds (default: 300)
    batch_size: Number of rows to fetch per batch for pagination (default: 1000)

Returns:
    QueryResult with headers, rows, and row_count
hue_run_query_to_csvA

Execute a SQL query and save results directly to a CSV file.

This is a convenience method that combines query execution with CSV export.
Ideal for exporting large result sets to files.

Args:
    statement: The SQL statement to execute
    filename: Output CSV filename (default: 'results.csv')
    dialect: SQL dialect - 'hive', 'sparksql', or 'impala' (default: 'hive')
    batch_size: Number of rows to fetch per batch (default: 1000)

Returns:
    OperationResult indicating success and the output filename
hue_export_and_downloadA

Execute an INSERT OVERWRITE DIRECTORY query and download the results.

This tool is for queries that write output to HDFS (like INSERT OVERWRITE DIRECTORY),
then downloads the resulting files to the local filesystem.

Args:
    statement: SQL statement with INSERT OVERWRITE DIRECTORY
    hdfs_directory: The HDFS directory where results are written
    local_directory: Local directory to download files to (default: '.')
    dialect: SQL dialect - 'hive', 'sparksql', or 'impala' (default: 'hive')
    file_pattern: Optional regex pattern to filter files to download
    timeout: Maximum wait time in seconds (default: 300)

Returns:
    OperationResult with list of downloaded files in message
hue_list_directoryA

List files and directories in an HDFS path.

Use this to browse the contents of HDFS directories.

Args:
    directory_path: The HDFS directory path (e.g., '/user/data', '/tmp')
    page_size: Maximum number of items to return (default: 1000)

Returns:
    DirectoryListing with path, items, and total_count
hue_check_directory_existsA

Check if a directory exists in HDFS.

Args:
    directory_path: The HDFS directory path to check

Returns:
    True if the directory exists, False otherwise
hue_download_fileA

Download a single file from HDFS.

Args:
    remote_path: The full path to the file in HDFS
    local_filename: Local filename to save as (optional, defaults to original name)

Returns:
    OperationResult with the local filename where file was saved
hue_download_directoryA

Download all files from an HDFS directory.

Args:
    directory_path: The HDFS directory path to download from
    local_directory: Local directory to save files to (default: '.')
    file_pattern: Optional regex pattern to filter files (e.g., '.*\.csv')

Returns:
    OperationResult with list of downloaded files
hue_upload_fileA

Upload a local file to HDFS.

Args:
    local_file_path: Path to the local file to upload
    hdfs_destination: Destination directory in HDFS

Returns:
    OperationResult indicating success

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored across 8 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap. For example, hue_check_directory_exists verifies existence, hue_list_directory browses contents, hue_download_file handles single files, hue_download_directory handles directories, hue_upload_file uploads, hue_execute_query runs queries, hue_export_and_download handles INSERT queries with downloads, and hue_run_query_to_csv exports directly to CSV. The descriptions clearly differentiate their specific use cases.

Naming Consistency5/5

All tools follow a consistent 'hue_verb_noun' pattern with snake_case throughout. The verbs are descriptive and appropriate for each action (e.g., check, download, execute, export, list, run, upload). There are no deviations in naming conventions across the toolset.

Tool Count5/5

With 8 tools, this server is well-scoped for its purpose of interacting with HDFS and executing queries via Hue. The count covers essential operations like file management (upload, download, list, check) and query execution (execute, export, run to CSV) without being excessive. Each tool serves a clear, necessary function in the workflow.

Completeness4/5

The toolset provides strong coverage for core HDFS file operations and SQL query execution, including CRUD-like actions for files and data retrieval. Minor gaps exist, such as no direct tool for deleting files/directories in HDFS or updating queries, but agents can work around these using existing tools (e.g., overwriting with upload or using INSERT queries). The surface supports common workflows effectively.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources