Which integrations are available for this server?

Provides tools for interacting with Cloudera Data Visualization (CDV) API, enabling management of groups, users, roles, segments, filter associations, workspaces, datasets, visuals, data connections, jobs, migrations, and debugging operations.

How do I use Cloudera Data Visualization MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Cloudera Data Visualization MCP Server list all workspaces" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Cloudera Data Visualization MCP Server

by kevintalbert

Overview Schema Related Servers Score Discussions

Python

Remote

Cloudera Data Visualization MCP Server

A Model Context Protocol server that exposes the full Cloudera Data Visualization (CDV) REST API to AI agents. This lets LLMs list, create, update, and delete CDV resources—groups, users, roles, segments, filter associations, workspaces, datasets, visuals, and data connections—as well as run jobs, query the data API, import/export migrations, and perform operational debugging tasks.

Tools

Groups

Tool	Description
`list_groups`	List all groups
`get_group(object_id)`	Get a group by ID
`create_group(body)`	Create a new group
`update_group(object_id, body)`	Update a group by ID
`delete_group(object_id)`	Delete a group by ID

Users

Tool	Description
`list_users`	List all users
`get_user(object_id)`	Get a user by ID
`create_user(body)`	Create a new user
`update_user(object_id, body)`	Update a user by ID
`delete_user(object_id)`	Delete a user by ID
`edit_user_profile(username, body)`	Edit a user's profile by username

Roles

Tool	Description
`list_roles`	List all roles
`get_role(object_id)`	Get a role by ID
`create_role(body)`	Create a new role
`update_role(object_id, body)`	Update a role by ID
`delete_role(object_id)`	Delete a role by ID

Segments

Tool	Description
`list_segments`	List all segments
`get_segment(object_id)`	Get a segment by ID
`create_segment(body)`	Create a new segment
`update_segment(object_id, body)`	Update a segment by ID
`delete_segment(object_id)`	Delete a segment by ID

Filter Associations

Tool	Description
`list_filter_associations`	List all filter associations
`get_filter_association(object_id)`	Get a filter association by ID
`create_filter_association(body)`	Create a new filter association
`update_filter_association(object_id, body)`	Update a filter association by ID
`delete_filter_association(object_id)`	Delete a filter association by ID

Workspaces

Tool	Description
`list_workspaces`	List all workspaces
`get_workspace(object_id)`	Get a workspace by ID
`create_workspace(body)`	Create a new workspace
`update_workspace(object_id, body)`	Update a workspace by ID
`delete_workspace(object_id)`	Delete a workspace by ID

Datasets

Tool	Description
`list_datasets`	List all datasets
`get_dataset(object_id)`	Get a dataset by ID
`create_dataset(body)`	Create a new dataset
`update_dataset(object_id, body)`	Update a dataset by ID
`delete_dataset(object_id)`	Delete a dataset by ID

Visuals

Tool	Description
`list_visuals`	List all visuals (charts/dashboards)
`get_visual(object_id)`	Get a visual by ID
`create_visual(body)`	Create a new visual (raw API body)
`update_visual(object_id, body)`	Update a visual by ID
`delete_visual(object_id)`	Delete a visual by ID
`create_smart_visual(dataset_id, visual_type, title, columns, filters?)`	Create a visual via the Smart Visual API with column/dimension inference

Supported visual_type values: trellis-bars, trellis-groupedbars, trellis-lines, trellis-areas, scatter, packed-bubbles, pie, radial, chord, leaflet, kpi, gauge, bullet, histogram, boxplot, table, crosstab, sparklines, treemap, dendrogram, network, combo, corelation, corelation-flow, calendar-heatmap, dashboard

Note: generic bars is not a valid type. Use trellis-bars for bar charts.

Connections

Tool	Description
`list_connections`	List all data connections
`get_connection(object_id)`	Get a connection by ID
`create_connection(body)`	Create a new connection
`update_connection(object_id, body)`	Update a connection by ID
`delete_connection(object_id)`	Delete a connection by ID
`export_connection(object_id)`	Export a connection definition by ID

Migrations

Tool	Description
`export_migration`	Export all CDV artifacts as a migration bundle
`import_migration(body)`	Import a CDV migration bundle

Data API

Tool	Description
`query_dataapi_get(params)`	Query `/apps/dataapi` via GET with optional parameters
`query_dataapi_post(body)`	Query `/apps/dataapi` via POST with a JSON body
`query_data_get(params)`	Query `/api/data` via GET with optional parameters
`query_data_post(body)`	Query `/api/data` via POST with a JSON body

Jobs

Tool	Description
`run_job(body)`	Trigger a job run
`run_extract(body)`	Run an existing extract job
`create_extract(body)`	Create a new extract job definition

Debugging / Operations

Tool	Description
`get_gc_monitor`	Retrieve GC monitor statistics
`post_gc_monitor(body)`	Trigger a GC monitor action
`get_gc_stats`	Retrieve GC statistics
`post_gc_stats(body)`	Trigger a GC stats action
`get_log_levels`	Get log levels for all loggers
`set_log_level(body)`	Set the default log level
`get_logger_level(logger_name)`	Get log level for a specific logger
`set_logger_level(logger_name, body)`	Set log level for a specific logger
`get_toggle_cprofile`	Get current cProfile tracing state
`toggle_cprofile(body)`	Toggle cProfile tracing on/off
`reset_dataconnection_cache(connection_id)`	Reset the cache for a data connection
`reset_dataset_cache(dataset_id)`	Reset the cache for a dataset

Environment Variables

Variable	Required	Description
`CDV_BASE_URL`	Yes	Base URL of your CDV deployment (e.g. `https://my-cdv.example.com`)
`CDV_API_KEY`	Yes	CDV API key — sent as `Authorization: apikey <key>`
`MCP_TRANSPORT`	No	Transport protocol: `stdio` (default), `http`, or `sse`

Usage with Claude Desktop

Add the following to the mcpServers section of your claude_desktop_config.json:

Option 1: Direct installation from GitHub (Recommended)

{
  "mcpServers": {
    "cdv-mcp-server": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/kevintalbert/cdv-mcp-server@main",
        "run-server"
      ],
      "env": {
        "CDV_BASE_URL": "https://my-cdv-instance.example.com",
        "CDV_API_KEY": "your-api-key-here"
      }
    }
  }
}

Option 2: Local installation (after cloning the repository)

{
  "mcpServers": {
    "cdv-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/CDV-MCP-Server",
        "run",
        "src/cdv_mcp_server/server.py"
      ],
      "env": {
        "CDV_BASE_URL": "https://my-cdv-instance.example.com",
        "CDV_API_KEY": "your-api-key-here"
      }
    }
  }
}

For Option 2, replace /path/to/CDV-MCP-Server with your local path.

Local Development

# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install dependencies
uv sync

# Run the server (stdio transport, default)
uv run run-server

# Run with HTTP transport
MCP_TRANSPORT=http uv run run-server

You can also create a .env file in the project root with your credentials:

CDV_BASE_URL=https://my-cdv-instance.example.com
CDV_API_KEY=your-api-key-here

Transport

The MCP server's transport protocol is configurable via the MCP_TRANSPORT environment variable:

stdio (default) — communicate over standard input/output. Useful for local tools, CLI scripts, and integrations like Claude Desktop.
http — expose an HTTP server. Useful for web-based deployments and microservices.
sse — use Server-Sent Events (SSE) transport. Useful for existing web-based deployments that rely on SSE.

Authentication

All requests to the CDV API are authenticated with the Authorization: bearer <CDV_API_KEY> header. The server first establishes a session by calling arc/apps with that token (which sets session cookies), then uses that session for all subsequent admin API calls — matching the CDV CML API v2 authentication pattern.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Resources

GitHub Repository

Need Help?

Related Servers

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

Lightport: Open-Sourcing Glama's AI Gateway
By punkpeye on April 27, 2026.
open source
OpenAI
Tool Definition Quality Score (TDQS)
By punkpeye on April 3, 2026.
mcp
The Hackers Who Tracked My Sleep Cycle
By punkpeye on March 26, 2026.
security

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kevintalbert/CDV-MCP-Server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server