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grafana

Grafana UI MCP Server

Official
by grafana

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'grafana_ui' has a clearly defined purpose that encompasses all Grafana UI-related operations.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'grafana_ui' follows a clear and descriptive pattern, and there are no other tools to compare it against for inconsistency.

    Tool Count2/5

    A single tool for a server named 'Grafana UI MCP Server' suggests a very thin or overly broad surface. Grafana UI likely involves multiple components (e.g., dashboards, panels, themes, documentation), which would typically warrant more granular tools (e.g., 3-15 tools) for effective agent use. One tool risks being a 'kitchen sink' that may not provide sufficient detail or control.

    Completeness2/5

    The tool description mentions accessing 'components, documentation, themes, and metadata,' but with only one tool, it's unclear how comprehensively these areas are covered. Likely, there are significant gaps in operations (e.g., no specific tools for creating dashboards, updating themes, or querying documentation), making the surface incomplete for typical Grafana UI workflows.

  • Average 2.6/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    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 behavioral disclosure. It mentions 'accessing' resources but doesn't describe whether operations are read-only, require authentication, have rate limits, or what the output format might be. For a tool with 10 parameters and multiple actions, this lack of behavioral context is a significant gap, leaving the agent uncertain about safety and performance implications.

    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, efficient sentence that lists the key resource types (components, documentation, themes, metadata) without unnecessary details. It's appropriately sized for a high-level overview, though it could be more front-loaded with a clearer verb. There's no wasted text, making it concise, but the structure lacks prioritization of the most common or critical actions.

    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 complexity (10 parameters, 11 possible actions) and lack of annotations or output schema, the description is incomplete. It doesn't address behavioral traits, usage scenarios, or output expectations, leaving the agent with insufficient context to invoke the tool effectively. The high schema coverage helps with parameters, but overall completeness is poor due to missing operational and safety information.

    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 input schema fully documents all 10 parameters with descriptions and enums. The description adds no additional meaning beyond the schema, such as explaining parameter interactions or providing examples. With high schema coverage, the baseline score is 3, as the description doesn't compensate but also doesn't detract from the schema's completeness.

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

    Purpose3/5

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

    The description states the tool provides access to Grafana UI components, documentation, themes, and metadata, which gives a general purpose. However, it's vague about what 'accessing' entails (e.g., retrieving, listing, searching) and doesn't specify the scope of 'unified' beyond listing multiple resource types. With no sibling tools, differentiation isn't needed, but the purpose lacks specificity in verbs and operational details.

    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, prerequisites, or contextual constraints. It lists resource types but doesn't indicate scenarios for choosing specific actions (e.g., 'get_component' vs 'list_components'). With no sibling tools, the absence of usage guidelines is a missed opportunity to clarify its role in a broader context.

    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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