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@mgcrea/mcp-grafana

by mgcrea

Grafana: Request

grafana_request
Read-only

Send read-only GET requests to any Grafana HTTP API endpoint not wrapped by named tools and return raw JSON cut at a chosen character limit.

Instructions

Escape hatch: GET any Grafana HTTP API endpoint the other tools do not wrap — /api/v1/provisioning/alert-rules/, /api/v1/provisioning/contact-points, /api/v1/provisioning/policies, /api/folders, /api/library-elements, /api/teams/search, /api/org/users, /api/dashboards/uid//versions, /apis/dashboard.grafana.app/v2beta1/namespaces/default/dashboards/. The answer is the raw JSON, unshaped, cut at max_chars. Read-only: only GET is ever sent. Prefer the named tools, which shape their output.

Input Schema

NameRequiredDescriptionDefault
pathYesAPI path, starting with /api/ or /apis/, e.g. "/api/v1/provisioning/contact-points".
paramsNoQuery parameters. A repeated parameter is an array: {"tag": ["a", "b"]}.
max_charsNoCut the serialized answer at this many characters (100-200000). Defaults to 20000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, it discloses that only GET is ever sent, the answer is raw unshaped JSON, and output is truncated at max_chars. These are important behavioral details for an open-world escape-hatch tool.

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 front-loaded with 'Escape hatch' and packs endpoint examples, safety, output shape, and alternative guidance into two dense sentences without filler.

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

Completeness5/5

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

For an open-world raw HTTP passthrough with no output schema, it covers the essential missing pieces: read-only behavior, unshaped JSON output, truncation, and when to prefer named tools. An agent has enough to call it correctly.

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 description coverage is 100%, so the schema already documents path, params, and max_chars well. The description reinforces usage with endpoint examples but does not add material parameter semantics beyond what the schema provides, making the baseline 3 appropriate.

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 explicitly calls itself an escape hatch for GET requests to Grafana HTTP API endpoints not covered by other tools, and it lists concrete endpoint families. This clearly distinguishes it from the named siblings like grafana_query and grafana_get_dashboard.

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?

It states exactly when to use it — for endpoints the other tools do not wrap — and explicitly says to prefer the named tools, which shape their output. This gives an agent a clear routing rule and alternative.

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