create_saved_view

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SERVERQuintaDB SOURCEhttps://quintadb.com/mcp

Medium RISK CLASS

Category Write

Parameters 63 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/com-quintadb-mcp/create-saved-view.md

WHAT IT DOES

What create_saved_view does on QuintaDB

AI agents use create_saved_view to create or update resources in QuintaDB, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your QuintaDB environment.

Parameter	Type	Required	Description
`name`	string	Yes	Display name
`app_id`	string	Yes	Project ID (from list_projects)
`filters`	array	—	Масив умов фільтрації
`sort_by`	string	—	field_name або field_id для сортування
`entity_id`	string	Yes	Form ID (from list_forms or describe_project)
`order_asc`	boolean	—	true=ASC (default), false=DESC

Parameters from the server's own tool schema.

RISK

Why create_saved_view is rated Medium

An AI agent can call create_saved_view faster than any human can review: one bad instruction and it creates or modifies resources in QuintaDB by the hundred, each call as confident as the last.

Risk signalsHigh parameter count (10 properties)

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs create_saved_view safely

PolicyLayer is an MCP gateway: it sits between your AI agents and QuintaDB, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For create_saved_view, this is the rule to start with:

create_saved_view Rate-limited

create_saved_view stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_saved_view": {
      "limits": [
        {
          "counter": "create_saved_view_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect QuintaDB, apply this rule, and every create_saved_view call is checked against it from then on.

FAQ

Questions about create_saved_view

What does the create_saved_view tool do? +

What parameters does create_saved_view accept? +

create_saved_view accepts 6 parameters: name, app_id, filters, sort_by, entity_id, order_asc. Required: name, app_id, entity_id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on create_saved_view? +

Register the QuintaDB MCP server in PolicyLayer and add a rule for create_saved_view: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches QuintaDB. Nothing to install.

What risk level is create_saved_view? +

create_saved_view is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_saved_view? +

Yes. Add a rate_limit block to the create_saved_view rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block create_saved_view completely? +

Set action: deny in the PolicyLayer policy for create_saved_view. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides create_saved_view? +

create_saved_view is provided by the QuintaDB MCP server (https://quintadb.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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