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mcp-knowledge

by io.github.getgapup

operational_dashboards

Read-only

Dashboards opérationnels — Gapup agent-payable C-suite expertise (COO). Returns a structured, audited deliverable. Reference case: Qonto (5 départements · 12 KPIs) — 4 dashboards live en 3 semaines · time-to-décision -55%. Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
companyYes
techStackYes
departmentsYes
kpiRequestsYes
primaryDashboardToolNo

Schema Changelog

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

  1. Changed12 schema fields changed
    • addedInput schema / properties / company / properties
      Added value: +{
+  "name": {
+    "maxLength": 200,
+    "minLength": 2,
+    "type": "string"
+  },
+  "sector": {
+    "maxLength": 100,
+    "minLength": 2,
+    "type": "string"
+  }
+}
    • addedInput schema / properties / company / required
      Added value: +[
+  "name",
+  "sector"
+]
    • removedInput schema / properties / currentToolsLandscape
      Removed value: -{
-  "type": "object"
-}
    • addedInput schema / properties / departments / items
      Added value: +{
+  "maxLength": 60,
+  "type": "string"
+}
    • addedInput schema / properties / departments / maxItems
      Added value: +8
    • addedInput schema / properties / departments / minItems
      Added value: +1
    • removedInput schema / properties / implementationConstraints
      Removed value: -{
-  "type": "array"
-}
    • addedInput schema / properties / kpiRequests
      Added value: +{
+  "items": {
+    "properties": {
+      "currentTrackingMethod": {
+        "enum": [
+          "manual",
+          "spreadsheet",
+          "partial-tool",
+          "none"
+        ],
+        "type": "string"
+      },
+      "department": {
+        "maxLength": 60,
+        "minLength": 2,
+        "type": "string"
+      },
+      "frequency": {
+        "enum": [
+          "realtime",
+          "daily",
+          "weekly",
+          "monthly"
+        ],
+        "type": "string"
+      },
+      "name": {
+        "maxLength": 100,
+        "minLength": 2,
+        "type": "string"
+      }
+    },
+    "required": [
+      "name",
+      "department",
+      "currentTrackingMethod",
+      "frequency"
+    ],
+    "type": "object"
+  },
+  "maxItems": 12,
+  "minItems": 3,
+  "type": "array"
+}
    • removedInput schema / properties / objectives
      Removed value: -{
-  "type": "array"
-}
    • addedInput schema / properties / primaryDashboardTool
      Added value: +{
+  "enum": [
+    "metabase",
+    "tableau",
+    "powerbi",
+    "looker",
+    "grafana",
+    "notion",
+    "other",
+    "none"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / techStack
      Added value: +{
+  "items": {
+    "maxLength": 60,
+    "type": "string"
+  },
+  "maxItems": 10,
+  "minItems": 0,
+  "type": "array"
+}
    • addedInput schema / required
      Added value: +[
+  "company",
+  "departments",
+  "kpiRequests",
+  "techStack"
+]
  2. First observed

TDQS

C2.6/5.0
Behavior3/5

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

Annotations declare readOnlyHint=true and openWorldHint=true, which the description does not contradict. The description adds 'Inputs are validated server-side', which hints at validation behavior, but does not disclose the nature of the deliverable or any side effects. Given annotations already cover read-only and open-world, the description adds moderate value.

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

Conciseness3/5

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

The description is short (3 sentences) but includes a reference case that may not be essential. It is moderately concise but lacks a clear initial statement of purpose; the title and first sentence are somewhat front-loaded, but the jargon reduces clarity.

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?

The tool has a complex input schema with nested objects and 6 parameters, but the description does not explain the output format or return value (no output schema). The brief description is insufficient for an agent to understand the tool's capabilities and limitations.

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?

Schema description coverage is low (17%), but the description does not explain any parameter meanings beyond what is in the schema. The reference case provides an example but not parameter-level details. The description should compensate for the schema gap but fails to do so.

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 mentions 'Returns a structured, audited deliverable' and the title 'Dashboards opérationnels' suggest the tool provides operational dashboards, but the verb is ambiguous (returns vs creates). The reference case implies dashboard generation, but the purpose is not explicitly stated. Distinguishing from hundreds of siblings is not achieved.

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 on when to use this tool vs alternatives. The only usage hint is 'Inputs are validated server-side — send the documented case fields', which is a procedural note, not a when-to-use or when-not-to-use directive.

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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TDQS

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

Resources