// SCAN REPORT

Cloudera Data Visualization MCP Server

66 tools. 41 can modify or destroy data without limits.

9 destructive tools with no built-in limits. Policy required.

Last updated:

41 can modify or destroy data
25 read-only
66 tools total

Community server · catalogue entry verified 03/07/2026

How to control Cloudera Data Visualization MCP Server ↓

TOOL MAP

What Cloudera Data Visualization MCP Server exposes to your agents

Read (25) Write / Execute (32) Destructive / Financial (9)

Running more than one server? Check your whole stack →

MOST DANGEROUS TOOLS
Critical Risk

The most dangerous Cloudera Data Visualization MCP Server tools

Destructive · High delete_connection The delete_connection tool permanently removes a data connection, which cannot be undone. Destructive · High delete_dataset This tool permanently removes data (a dataset) from the Cloudera Data Visualization system. Destructive · High delete_filter_association This tool irreversibly removes a filter association, which is a configuration object that cannot be easily restored without manual intervention or backups. Destructive · High delete_group Deleting a group is a destructive operation that cannot be undone.

41 of Cloudera Data Visualization MCP Server's 66 tools can modify, destroy, or commit something on every call — and an agent calls them with no built-in limits.

POLICY

How to control Cloudera Data Visualization MCP Server

PolicyLayer is an MCP gateway — it sits between your AI agents and Cloudera Data Visualization MCP Server, and nothing reaches the server without passing your rules. These are the rules we recommend:

Deny destructive operations
{
  "delete_connection": {
    "deny_if": [
      {
        "conditions": [],
        "on_deny": "Blocked by default. Requires approval."
      }
    ]
  }
}

Destructive tools should never be available to autonomous agents without human approval.

Rate limit write operations
{
  "create_connection": {
    "limits": [
      {
        "counter": "create_connection_per_hour",
        "window": "hour",
        "max": 30,
        "scope": "grant"
      }
    ]
  }
}

Prevents bulk unintended modifications from agents caught in loops.

Cap read operations
{
  "export_connection": {
    "limits": [
      {
        "counter": "export_connection_per_minute",
        "window": "minute",
        "max": 60,
        "scope": "grant"
      }
    ]
  }
}

Controls API costs and prevents retry loops from exhausting upstream rate limits.

  1. Create a free account and register Cloudera Data Visualization MCP Server — nothing to install.
  2. Add these rules — paste them, or build them visually. Tune the limits to your setup.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
ENFORCE POLICY ON CLOUDERA DATA VISUALIZATION →

Instant setup, no code required.

FULL CATALOGUE

All 66 Cloudera Data Visualization MCP Server tools

DESTRUCTIVE 9 tools
Destructive delete_connection Delete a CDV data connection by its numeric ID. Destructive delete_dataset Delete a CDV dataset by its numeric ID. Destructive delete_filter_association Delete a CDV filter association by its numeric ID. Destructive delete_group Delete a CDV group by its numeric ID. Destructive delete_role Delete a CDV role by its numeric ID. Destructive delete_segment Delete a CDV segment by its numeric ID. Destructive delete_visual Delete a CDV visual or dashboard by its numeric ID. Destructive delete_workspace Delete a CDV workspace by its numeric ID. Destructive reset_dataset_cache Reset the query result cache for a specific CDV dataset. Requires ds_manage permission.
EXECUTE 8 tools
Execute query_dataapi query_dataapi Execute reset_dataconnection_cache Reset the query result cache for a specific CDV data connection. Requires ds_manage permission. Execute run_extract Run one or more CDV data extract jobs by their comma-separated IDs. Execute run_job Trigger a rerun of one or more CDV scheduled jobs. Execute set_gc_monitor Enable or disable GC monitoring on the CDV server. Execute set_gc_stats Set GC debug flags on the CDV server. Requires sys_viewlogs permission. Execute set_logger_level Set the log level for a specific named logger. Requires sys_viewlogs permission. Execute toggle_cprofile Toggle cProfile profiling on/off for a CDV server function. Requires sys_viewlogs permission.
WRITE 24 tools
Write create_connection create_connection Write create_dashboard create_dashboard Write create_dataset create_dataset Write create_extract create_extract Write create_filter_association Create a new CDV filter association linking a segment to users or groups. Write create_group Create a new CDV group. Write create_role Create a new CDV role. body fields: name, permissions (list). Write create_segment Create a new CDV row-level security segment. body fields: name, filter_definition. Write create_smart_visual create_smart_visual Write create_visual Create a CDV visual using the raw admin API. Write create_workspace Create a new CDV workspace. Write edit_user_profile Edit the profile of a CDV user identified by username (e.g. update email, name). Write export_migration Export all CDV visual artifacts (dashboards, datasets, connections) as a migration bundle. Write import_migration Import a CDV migration bundle. Write set_log_level Set the log level for the root logger. Requires sys_viewlogs permission. Write update_connection Update an existing CDV data connection by its numeric ID. Write update_dataset Update an existing CDV dataset by its numeric ID. Write update_filter_association Update an existing CDV filter association by its numeric ID. Write update_group Update an existing CDV group by its numeric ID. Provide fields to change (e.g. name, users). Write update_role Update an existing CDV role by its numeric ID. Write update_segment Update an existing CDV segment by its numeric ID. Write update_user Update an existing CDV user by their numeric ID. Write update_visual Update an existing CDV visual by its numeric ID. Write update_workspace Update an existing CDV workspace by its numeric ID.
READ 25 tools
Read export_connection Export a CDV data connection definition by its numeric ID. Read get_connection Get a single CDV data connection by its numeric ID. Read get_dataset Get a single CDV dataset by its numeric ID. Read get_filter_association Get a single CDV filter association by its numeric ID. Read get_gc_monitor Check whether GC monitoring is currently enabled on the CDV server. Read get_gc_stats Retrieve the current GC debug flags from the CDV server. Read get_group Get a single CDV group by its numeric ID. Read get_log_levels Retrieve the current log level for the root logger on the CDV server. Read get_logger_level Retrieve the current log level for a specific logger by name. Read get_role Get a single CDV role by its numeric ID. Read get_segment Get a single CDV segment by its numeric ID. Read get_toggle_cprofile Check whether cProfile profiling is enabled for a CDV server function. Read get_user Get a single CDV user by their numeric ID. Read get_visual Get a single CDV visual by its numeric ID. Read get_workspace Get a single CDV workspace by its numeric ID. Read list_connections list_connections Read list_datasets list_datasets Read list_filter_associations List all filter associations (segment-to-user/group mappings) defined in CDV. Read list_groups List all groups defined in CDV. Read list_roles List all roles defined in CDV. Read list_segments List all row-level security segments defined in CDV. Read list_users List all users defined in CDV. Read list_visuals list_visuals Read list_workspaces list_workspaces Read query_enhanced_data_api Query data via the CDV Enhanced Data API (/api/data).
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FAQ

Questions about Cloudera Data Visualization MCP Server

Can an AI agent delete data through the Cloudera Data Visualization MCP Server MCP server? +

Yes. The Cloudera Data Visualization MCP Server server exposes 9 destructive tools including delete_connection, delete_dataset, delete_filter_association. These permanently remove resources with no undo. PolicyLayer blocks destructive tools by default so they never reach the upstream server.

How do I prevent bulk modifications through Cloudera Data Visualization MCP Server? +

The Cloudera Data Visualization MCP Server server has 24 write tools including create_connection, create_dashboard, create_dataset. Set a rate limit in your policy -- for example, 10 calls per hour prevents an agent from making more than 10 modifications per hour. PolicyLayer enforces this at the gateway, before calls reach Cloudera Data Visualization MCP Server.

How many tools does the Cloudera Data Visualization MCP Server MCP server expose? +

66 tools across 4 categories: Destructive, Execute, Read, Write. 25 are read-only. 41 can modify, create, or delete data.

How do I enforce a policy on Cloudera Data Visualization MCP Server? +

Register the Cloudera Data Visualization MCP Server MCP server in PolicyLayer, apply the suggested rules above (adjust the limits to your use case), and point your AI client at the PolicyLayer proxy URL instead of the server directly. Your agents keep the same tools; PolicyLayer evaluates every call against policy before it executes. Nothing to install, live in minutes.

Enforce policy on every Cloudera Data Visualization MCP Server tool call.

Deterministic rules across all 66 Cloudera Data Visualization MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

ENFORCE POLICY ON CLOUDERA DATA VISUALIZATION →

Instant setup, no code required.

66 Cloudera Data Visualization MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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