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lukleh

mcp-read-only-grafana

by lukleh

get_dashboard

Retrieve a full Grafana dashboard definition with all panels and settings. For large dashboards, use the panel-specific workflow to avoid response limits.

Instructions

Get full dashboard definition including all panels and settings.

WARNING: Large dashboards (>50 panels) will likely exceed MCP response limits (25,000 tokens). For large dashboards, use this workflow instead:

  1. get_dashboard_info() - Get overview and panel list

  2. get_dashboard_panel() - Get details for specific panels of interest

Args: connection_name: Name of the Grafana connection dashboard_uid: UID of the dashboard to retrieve

Returns: JSON string with complete dashboard definition.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dashboard_uidYes
connection_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.4.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It implies a read-only retrieval operation and states the return format, but it does not explicitly confirm there are no side effects, nor does it mention authentication, permissions, or rate limits. The behavior is mostly inferable from the word 'get' but not fully explicit.

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 well-structured and reasonably concise. The warning and workflow guidance are valuable and not excessive, and the Args/Returns sections are clear. It could be slightly tighter, but the content is purposeful and easy to scan.

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

Completeness3/5

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

The description states that the tool returns a JSON string with the complete dashboard definition, which is sufficient for basic use. However, it does not mention error conditions, how the connection_name is resolved, or whether the output is structured in a particular schema. It is adequate but leaves some operational context unspecified.

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

Parameters2/5

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

The input schema provides no descriptions (0% coverage) and the Args section in the description merely repeats the parameter names without adding detail. While 'connection_name' and 'dashboard_uid' are somewhat self-explanatory, the description does not explain their format, source, or how they are used, so it fails to compensate for the missing schema coverage.

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

Purpose5/5

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

The description clearly states the tool retrieves the full dashboard definition including all panels and settings, and the 'get' verb makes the operation unambiguous. It also implicitly distinguishes itself from related sibling tools like get_dashboard_info and get_dashboard_panel by specifying the complete payload.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool versus alternatives: it warns that dashboards with more than 50 panels may exceed response limits and directs users to a two-step workflow with get_dashboard_info and get_dashboard_panel. This is concrete, actionable, and distinguishes it from sibling tools.

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

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