enps_auto
eNPS automatisé — Gapup agent-payable C-suite expertise (CHRO). Returns a structured, audited deliverable. Reference case: BlaBlaCar — eNPS pulse mensuel · 700 FTE 8 pays · segments × tenure × manager · plays correctifs ciblés. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-gapup-mcp/enps-auto.md
What enps_auto does on Gapup Mcp
AI agents use enps_auto to commit financial operations through Gapup Mcp, usually the final step of a payment, billing, or trading workflow. A call moves real money.
| 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 |
focus | string | — | |
company | object | Yes | |
context | object | Yes | |
toolStack | object | Yes | |
segmentation | object | Yes | |
presenterScript | array | — |
Parameters from the server's own tool schema.
Why enps_auto is rated Critical
The server explicitly states tools are 'agent-payable' with 'x402 per-call' billing. The tool description confirms it is 'agent-payable', meaning each invocation by an AI agent commits a financial transaction (micropayment). The underlying function (eNPS/employee pulse survey analysis) is a Read/Write operation, but the payment-on-call mechanism elevates this to Financial category per the severity hierarchy.
From the tool's definition Gapup agent-payable C-suite expertise; x402 per-call (from server description); 'agent-payable' in tool description
Risk signalsHigh parameter count (29 properties)
Attacks that exploit this kind of access
The rule that runs enps_auto 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 enps_auto, this is the rule to start with:
Any call to enps_auto is blocked until a human approves it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every enps_auto call is checked against it from then on.
Questions about enps_auto
eNPS automatisé — Gapup agent-payable C-suite expertise (CHRO). Returns a structured, audited deliverable. Reference case: BlaBlaCar — eNPS pulse mensuel · 700 FTE 8 pays · segments × tenure × manager · plays correctifs ciblés. Inputs are validated server-side — send the documented case fields. It is categorised as a Financial tool in the Gapup Mcp MCP Server, which means it involves financial transactions. Block by default and require explicit approval.
enps_auto accepts 7 parameters: async, focus, company, context, toolStack, segmentation, presenterScript. Required: company, context, toolStack, segmentation. 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 enps_auto: 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.
enps_auto is a Financial tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the enps_auto 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 enps_auto. 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.
enps_auto 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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