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lukleh

mcp-read-only-grafana

by lukleh

explore_query

Execute a Grafana Explore query using the specified connection and query definitions, returning the JSON response.

Instructions

Execute a Grafana Explore query via the /api/ds/query endpoint.

Args: connection_name: Name of the Grafana connection queries: List of Explore query definitions to execute range_from: Optional relative or absolute start time (e.g., 'now-6h') range_to: Optional end time (e.g., 'now') max_data_points: Optional maximum number of datapoints to request interval_ms: Optional query interval in milliseconds additional_options: Extra fields to merge into the request body

Returns: JSON string with the query response payload.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYes
range_toNo
range_fromNo
interval_msNo
connection_nameYes
max_data_pointsNo
additional_optionsNo

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

B3/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It does not mention whether the operation is read-only, whether it can trigger side effects, auth requirements, rate limits, or any other safety-relevant behavior.

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

Conciseness5/5

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

The description is concise, well-structured with an Args section, and includes a clear Returns note. Every sentence serves a purpose and there is no redundant or misleading content.

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 covers the parameters and return type at a basic level, but lacks detail about the expected structure of a query definition, the exact response format, error behavior, or how this endpoint differs from other query tools. It is adequate for a simple use case but not fully complete for a complex Explore query.

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

Parameters4/5

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

The description gives a brief explanation for every parameter, including meaning for range_from, range_to, max_data_points, interval_ms, and additional_options. This adds useful semantics beyond the raw schema, though some explanations like 'query definitions' and 'extra fields' remain somewhat vague.

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 ('Execute') and the resource ('a Grafana Explore query via the /api/ds/query endpoint'). However, it does not explicitly differentiate this generic Explore query capability from the more specific sibling tools like query_prometheus and query_loki.

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?

No guidance is provided about when to use this tool versus the alternative query tools, or when it would be inappropriate to use. There is no explicit scoping, exclusions, or alternative recommendations.

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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