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mcp-knowledge

by io.github.getgapup

account_expansion_mapper

Read-only

Mapping d'expansion comptes — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Notion B2B Enterprise — top 30 strategic accounts · expansion plays NRR 130%+ target · Snowflake/Shopify/Vercel/Stripe analyzed. 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.
focusNo
companyYes
accountsYes
ownershipYes

Schema Changelog

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

  1. Changed9 schema fields changed
    • addedInput schema / properties / accounts / items
      Added value: +{
+  "properties": {
+    "accountName": {
+      "maxLength": 160,
+      "minLength": 2,
+      "type": "string"
+    },
+    "contractRenewalDate": {
+      "type": "string"
+    },
+    "currentArrEur": {
+      "minimum": 0,
+      "type": "number"
+    },
+    "currentSeats": {
+      "minimum": 0,
+      "type": "integer"
+    },
+    "knownTriggers": {
+      "maxLength": 400,
+      "type": "string"
+    },
+    "modulesAdopted": {
+      "items": {
+        "type": "string"
+      },
+      "maxItems": 15,
+      "minItems": 1,
+      "type": "array"
+    },
+    "segment": {
+      "enum": [
+        "enterprise",
+        "mid-market",
+        "smb"
+      ],
+      "type": "string"
+    },
+    "usageScore": {
+      "enum": [
+        "heavy",
+        "active",
+        "light",
+        "dormant"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "accountName",
+    "segment",
+    "currentArrEur",
+    "currentSeats",
+    "modulesAdopted",
+    "contractRenewalDate",
+    "usageScore"
+  ],
+  "type": "object"
+}
    • addedInput schema / properties / accounts / maxItems
      Added value: +50
    • addedInput schema / properties / accounts / minItems
      Added value: +5
    • addedInput schema / properties / company / properties
      Added value: +{
+  "arrTotalEur": {
+    "minimum": 0,
+    "type": "number"
+  },
+  "name": {
+    "maxLength": 120,
+    "minLength": 2,
+    "type": "string"
+  },
+  "nrrCurrent": {
+    "maximum": 200,
+    "minimum": 50,
+    "type": "number"
+  },
+  "nrrTarget": {
+    "maximum": 200,
+    "minimum": 50,
+    "type": "number"
+  },
+  "sector": {
+    "maxLength": 120,
+    "minLength": 2,
+    "type": "string"
+  }
+}
    • addedInput schema / properties / company / required
      Added value: +[
+  "name",
+  "sector",
+  "arrTotalEur",
+  "nrrCurrent",
+  "nrrTarget"
+]
    • addedInput schema / properties / focus / maxLength
      Added value: +400
    • addedInput schema / properties / ownership / properties
      Added value: +{
+  "aeTeamSize": {
+    "minimum": 1,
+    "type": "integer"
+  },
+  "averageQuotaPerAeEur": {
+    "minimum": 0,
+    "type": "number"
+  },
+  "csmTeamSize": {
+    "minimum": 1,
+    "type": "integer"
+  }
+}
    • addedInput schema / properties / ownership / required
      Added value: +[
+  "aeTeamSize",
+  "csmTeamSize",
+  "averageQuotaPerAeEur"
+]
    • addedInput schema / required
      Added value: +[
+  "company",
+  "accounts",
+  "ownership"
+]
  2. First observed

TDQS

C2.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is clear. The description adds 'returns a structured, audited deliverable' but no additional behavioral details like auth needs or rate limits.

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 relatively short but includes a reference case that may not be essential. It is front-loaded with the title but contains jargon that 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?

Given the complex nested schema and no output schema, the description is incomplete. It does not explain the deliverable's format, interpretation, or prerequisites, leaving significant gaps.

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%. The description does not explain parameters beyond 'send the documented case fields,' failing to compensate for the low schema coverage.

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 gives a sense of account expansion mapping for B2B CRO but uses jargon ('Gapup agent-payable C-suite expertise') and a French title without a clear English verb. It doesn't differentiate from sibling tools like upsell_hunter or abm_architect.

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 versus alternatives. Only mentions server-side validation but lacks context for selection among similar tools.

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