Looker MCP Server

add_dashboard_filter

Add a filter to a Looker dashboard by specifying the dashboard ID, filter title, and dimension. Optionally set filter type and default value.

Instructions

Add a filter to a dashboard.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dashboard_id": "<dashboard_id>",
      "title": "<title>",
      "dimension": "<dimension>"
    },
    "name": "add_dashboard_filter"
  }
}

Input Schema

Name	Required	Description	Default
`dashboard_id`	Yes	ID of the dashboard
`title`	Yes	Filter display title
`dimension`	Yes	Fully-qualified dimension name (e.g. 'orders.region')
`type`	No	Filter type: 'field_filter', 'date_filter'	field_filter
`default_value`	No	Default filter value

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.20.0May 29, 2026

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description only states the action without disclosing behavioral traits such as whether the filter overrides existing ones, any required permissions, or side effects. This leaves the agent with insufficient information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no unnecessary words. It is concise, though it lacks structural elements like headings or examples.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and 5 parameters (3 required), the description is too minimal. It does not explain the filter's effect on the dashboard or the return value, which an agent needs for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all 5 parameters, so the baseline is 3. The description adds no additional meaning beyond the schema, but it does not harm clarity either.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action and resource (add a filter to a dashboard), and it distinguishes from sibling tools like 'add_dashboard_element' which add other elements. However, it is brief and could be more specific about what kind of filter.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives (e.g., update_dashboard or add_dashboard_element). There is no context about prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.