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mcp-knowledge

by io.github.getgapup

event_marketing

Read-only

Marketing événementiel — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Pennylane (€120k/an budget événements) — 7 événements sélectionnés · coût-MQL -38% vs année précédente. 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
teamSizeYes
geographyYes
objectivesYes
currentEventsYes
targetAudienceYes
annualBudgetEurYes

TDQS

C2.4/5.0
Behavior2/5

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

Description adds minimal behavioral context beyond annotations. readOnlyHint and openWorldHint are provided but not explained; description does not address permissions, rate limits, or side effects. 'Audited deliverable' suggests reliability but no further detail.

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?

Description is two sentences plus a case study, which adds length without aiding function clarity. The first sentence is a tagline rather than a clear verb+resource. Could be more concise and front-loaded.

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 8 parameters, 7 required, nested objects, and no output schema, the description is insufficient. It does not explain the return structure or how parameters relate. The case study offers some context but not enough for complete understanding.

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?

With only 13% schema description coverage, the description should compensate but does not. It mentions 'send the documented case fields' without elaborating on parameters. The schema has many required fields, but description adds no guidance on values or format.

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 it returns a 'structured, audited deliverable' related to event marketing, but does not specify the exact function (e.g., planning, analysis) or differentiate from siblings like customer_marketing. The phrase 'Gapup agent-payable C-suite expertise (CMO)' is vague.

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 on when to use this tool versus alternatives. The case study implies event marketing ROI analysis, but no criteria or exclusions are given. Sibling tools cover many marketing functions, but description lacks context for selection.

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