customer_marketing
Marketing clients & ambassadeurs — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Gapup Hub — 12 clients analysés · 4 ambassadeurs identifiés · Programme + 6 case studies + référral. Inputs are validated server-side — send the documented ca...
This record as markdown: /tools/io-github-getgapup-gapup-mcp/customer-marketing.md
What customer_marketing does on Gapup Mcp
AI agents use customer_marketing to create or update resources in Gapup Mcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Gapup Mcp environment.
| 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 |
goals | array | Yes | |
company | object | Yes | |
product | object | Yes | |
customers | array | Yes | |
targetUseCases | array | — | |
contentBudgetEur | number | — |
Parameters from the server's own tool schema.
Why customer_marketing is rated Medium
The tool appears to generate marketing deliverables (ambassador programs, case studies, referral programs) based on client analysis. This is best classified as Write since it creates structured output documents/programs. It does not clearly execute code, destroy data, or move money.
From the tool's definition Marketing clients & ambassadeurs — Returns a structured, audited deliverable. Reference case: 12 clients analysés · 4 ambassadeurs identifiés · Programme + 6 case studies + référral.
Risk signalsHigh parameter count (20 properties)
Attacks that exploit this kind of access
The rule that runs customer_marketing safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For customer_marketing, this is the rule to start with:
customer_marketing stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every customer_marketing call is checked against it from then on.
Questions about customer_marketing
Marketing clients & ambassadeurs — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Gapup Hub — 12 clients analysés · 4 ambassadeurs identifiés · Programme + 6 case studies + référral. Inputs are validated server-side — send the documented case fields. It is categorised as a Write tool in the Gapup Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
customer_marketing accepts 7 parameters: async, goals, company, product, customers, targetUseCases, contentBudgetEur. Required: goals, company, product, customers. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for customer_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 Gapup Mcp. Nothing to install.
customer_marketing is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the customer_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 customer_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.
customer_marketing is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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