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mcp-knowledge

by io.github.getgapup

funding_hunter

Read-only

Chasseur de financements — Gapup agent-payable C-suite expertise (CFO). Returns a structured, audited deliverable. Reference case: PME deeptech cleantech FR €8M CA — top 30 dispositifs BPI+France2030+EU+VC. 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
projectYes
financialsYes
preferencesYes

Schema Changelog

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

  1. Changed9 schema fields changed
    • addedInput schema / properties / company / properties
      Added value: +{
+  "countryHQ": {
+    "maxLength": 60,
+    "minLength": 2,
+    "type": "string"
+  },
+  "foundedYear": {
+    "maximum": 2030,
+    "minimum": 1990,
+    "type": "integer"
+  },
+  "name": {
+    "maxLength": 120,
+    "minLength": 2,
+    "type": "string"
+  },
+  "pitch": {
+    "maxLength": 800,
+    "minLength": 20,
+    "type": "string"
+  },
+  "sector": {
+    "maxLength": 120,
+    "minLength": 3,
+    "type": "string"
+  },
+  "siret": {
+    "type": "string"
+  },
+  "stage": {
+    "enum": [
+      "pre-seed",
+      "seed",
+      "series-a",
+      "series-b",
+      "growth"
+    ],
+    "type": "string"
+  }
+}
    • addedInput schema / properties / company / required
      Added value: +[
+  "name",
+  "pitch",
+  "foundedYear",
+  "countryHQ",
+  "sector",
+  "stage"
+]
    • addedInput schema / properties / financials / properties
      Added value: +{
+  "grossMarginPct": {
+    "maximum": 100,
+    "minimum": 0,
+    "type": "number"
+  },
+  "hasCIREligibility": {
+    "type": "boolean"
+  },
+  "hasJEI": {
+    "type": "boolean"
+  },
+  "headcount": {
+    "minimum": 0,
+    "type": "integer"
+  },
+  "rdSpendEur": {
+    "minimum": 0,
+    "type": "number"
+  },
+  "revenueEur": {
+    "minimum": 0,
+    "type": "number"
+  }
+}
    • addedInput schema / properties / financials / required
      Added value: +[
+  "revenueEur",
+  "rdSpendEur",
+  "headcount",
+  "grossMarginPct"
+]
    • addedInput schema / properties / preferences / properties
      Added value: +{
+  "maxDilutionPct": {
+    "maximum": 40,
+    "minimum": 0,
+    "type": "number"
+  },
+  "nonDilutiveFirst": {
+    "type": "boolean"
+  },
+  "urgencyDays": {
+    "maximum": 365,
+    "minimum": 30,
+    "type": "integer"
+  }
+}
    • addedInput schema / properties / preferences / required
      Added value: +[
+  "nonDilutiveFirst"
+]
    • addedInput schema / properties / project / properties
      Added value: +{
+  "budgetEur": {
+    "maximum": 50000000,
+    "minimum": 50000,
+    "type": "integer"
+  },
+  "description": {
+    "maxLength": 600,
+    "minLength": 20,
+    "type": "string"
+  },
+  "geographies": {
+    "items": {
+      "maxLength": 60,
+      "minLength": 2,
+      "type": "string"
+    },
+    "maxItems": 5,
+    "minItems": 1,
+    "type": "array"
+  },
+  "horizonMonths": {
+    "maximum": 36,
+    "minimum": 6,
+    "type": "integer"
+  },
+  "techReadinessLevel": {
+    "maximum": 9,
+    "minimum": 1,
+    "type": "integer"
+  }
+}
    • addedInput schema / properties / project / required
      Added value: +[
+  "description",
+  "budgetEur",
+  "horizonMonths",
+  "geographies"
+]
    • addedInput schema / required
      Added value: +[
+  "company",
+  "financials",
+  "project",
+  "preferences"
+]
  2. First observed

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint=true and openWorldHint=true, so the description's mention of server-side validation adds some context but does not significantly extend behavioral understanding. There is no contradiction with annotations.

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 concise with 4 sentences, but the reference case is overly specific and may not be helpful for general use. The structure is acceptable but the French phrasing could be streamlined.

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 is complex with nested objects and no output schema. The description fails to explain what the structured deliverable contains, how to handle validation errors, or any edge cases. Given the complexity, the description is incomplete.

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%, leaving many nested properties (e.g., company.siret, financials.hasJEI) undocumented. The description does not explain the purpose or expected values of parameters beyond a vague instruction to 'send the documented case fields'. This fails to compensate for the schema's gaps.

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 identifies the tool as a funding hunter that returns a structured deliverable, with a specific reference case. The French title 'Chasseur de financements' aligns with the English name, though the mix of languages may reduce clarity for non-French speakers. It distinguishes itself from sibling tools like 'capital_strategy' by focusing on actionable funding options.

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 explicit guidance is provided on when to use this tool versus alternatives. The description gives a reference case but does not explain prerequisites, contexts where the tool is most beneficial, or situations to avoid. Sibling tools are not compared.

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