Skip to main content
Glama

mcp-knowledge

by io.github.getgapup

vendor_risk_assessor

Read-only

Évaluateur de risque fournisseurs — Gapup agent-payable C-suite expertise (RISK). Returns a structured, audited deliverable. Reference case: Gapup Hub — 15 fournisseurs · €1.8M spend · 3 critiques · Heatmap + plan de remédiation. 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
vendorsYes
riskFrameworkNo
assessmentPurposeNo

Schema Changelog

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

  1. Changed8 schema fields changed
    • addedInput schema / properties / assessmentPurpose / enum
      Added value: +[
+  "annual-review",
+  "due-diligence",
+  "audit",
+  "board-report"
+]
    • addedInput schema / properties / company / properties
      Added value: +{
+  "isRegulated": {
+    "type": "boolean"
+  },
+  "name": {
+    "maxLength": 100,
+    "type": "string"
+  },
+  "sector": {
+    "maxLength": 100,
+    "type": "string"
+  }
+}
    • addedInput schema / properties / company / required
      Added value: +[
+  "name",
+  "sector"
+]
    • addedInput schema / properties / riskFramework / items
      Added value: +{
+  "enum": [
+    "cyber",
+    "financial",
+    "operational",
+    "regulatory",
+    "esg",
+    "concentration"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / vendors / items
      Added value: +{
+  "properties": {
+    "annualSpendEur": {
+      "minimum": 0,
+      "type": "number"
+    },
+    "category": {
+      "maxLength": 100,
+      "type": "string"
+    },
+    "contractExpiryMonths": {
+      "minimum": 0,
+      "type": "integer"
+    },
+    "criticality": {
+      "enum": [
+        "critical",
+        "important",
+        "standard",
+        "low"
+      ],
+      "type": "string"
+    },
+    "dataAccess": {
+      "type": "boolean"
+    },
+    "id": {
+      "maxLength": 20,
+      "type": "string"
+    },
+    "iso27001": {
+      "type": "boolean"
+    },
+    "knownIssues": {
+      "items": {
+        "maxLength": 200,
+        "type": "string"
+      },
+      "maxItems": 5,
+      "type": "array"
+    },
+    "name": {
+      "maxLength": 100,
+      "type": "string"
+    },
+    "soc2": {
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "id",
+    "name",
+    "category"
+  ],
+  "type": "object"
+}
    • addedInput schema / properties / vendors / maxItems
      Added value: +50
    • addedInput schema / properties / vendors / minItems
      Added value: +3
    • addedInput schema / required
      Added value: +[
+  "company",
+  "vendors"
+]
  2. First observed

TDQS

C2.9/5.0
Behavior3/5

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

The description adds that it returns a 'structured, audited deliverable' and that inputs are validated server-side. Annotations already declare readOnlyHint=true and openWorldHint=true, so the core behavioral traits are covered. The description provides minor additional context but does not contradict annotations.

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 relatively concise, with key information front-loaded. The reference case is useful but adds some verbosity. The mix of French and English may reduce clarity for English-only agents. Overall, it is efficiently structured but could be tighter.

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 tool's complexity (nested objects, 5 parameters, no output schema), the description is insufficient. It does not explain the deliverable's format, how results relate to inputs, or prerequisites. The reference case is anecdotal, not general guidance. The agent would need additional context to use this tool effectively.

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 only 20% (only 'async' has a description). The tool description does not explain any parameters, relying on 'send the documented case fields' which is vague. For a complex nested-object schema, this leaves the agent without sufficient semantic context to use parameters correctly.

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 it evaluates vendor risk and returns a structured deliverable. The verb 'Évaluateur de risque' and reference case give context. However, jargon like 'Gapup agent-payable C-suite expertise' and lack of explicit distinction from sibling tools like vendor_management or supplier_esg_audit prevent a perfect score.

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?

There is no guidance on when to use this tool versus alternatives. The phrase 'send the documented case fields' implies sending required parameters but offers no context on selection criteria or exclusions. Sibling tools cover similar domains, yet no differentiation is provided.

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

All mcp-knowledge toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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