event_marketing
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.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/event-marketing.md
What event_marketing does on Mcp Knowledge
AI agents call event_marketing to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
async | boolean | — | If 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 ti |
company | object | Yes | |
teamSize | number | Yes | |
geography | array | Yes | |
objectives | array | Yes | |
currentEvents | array | Yes | |
targetAudience | string | Yes | |
annualBudgetEur | number | Yes |
Parameters from the server's own tool schema.
Why event_marketing is rated Low
The tool appears to generate and return a structured marketing analysis deliverable based on validated input fields. It references a benchmark case (Pennylane) and outputs event marketing recommendations. This is primarily a Read/query-style operation that retrieves expert analysis. No evidence of code execution, data deletion, financial transactions, or irreversible data modification.
From the tool's definition Returns a structured, audited deliverable — event marketing analysis/recommendations for a given case (CMO expertise, budget/MQL analysis)
Risk signalsHigh parameter count (13 properties)
Attacks that exploit this kind of access
The rule that runs event_marketing safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For event_marketing, this is the rule to start with:
event_marketing is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every event_marketing call is checked against it from then on.
Questions about event_marketing
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. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
event_marketing accepts 8 parameters: async, company, teamSize, geography, objectives, currentEvents, targetAudience, annualBudgetEur. Required: company, teamSize, geography, objectives, currentEvents, targetAudience, annualBudgetEur. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for event_marketing: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Knowledge. Nothing to install.
event_marketing is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the event_marketing rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for event_marketing. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
event_marketing is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Mcp Knowledge, and thousands of servers like it.
This server
Across the catalogue