renewal_optimizer
Optimiseur de renouvellements — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — Renewals 10 comptes · €89k ARR à 90j · 3 comptes at-risk · Playbook 6 scénarios. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-gapup-mcp/renewal-optimizer.md
What renewal_optimizer does on Gapup Mcp
AI agents use renewal_optimizer 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 |
company | object | Yes | |
horizon | string | — | |
product | object | Yes | |
accounts | array | Yes | |
targetRenewalRatePct | number | — |
Parameters from the server's own tool schema.
Why renewal_optimizer is rated Critical
The tool explicitly deals with renewal optimization involving ARR (Annual Recurring Revenue), at-risk accounts, and financial playbooks. It is agent-payable (x402 per-call financial commitment) and directly influences financial decisions around contract renewals worth tens of thousands of euros.
From the tool's definition Optimiseur de renouvellements — agent-payable — €89k ARR à 90j — Playbook 6 scénarios — 3 comptes at-risk
Risk signalsHigh parameter count (22 properties)
Attacks that exploit this kind of access
The rule that runs renewal_optimizer 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 renewal_optimizer, this is the rule to start with:
Any call to renewal_optimizer 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 renewal_optimizer call is checked against it from then on.
Questions about renewal_optimizer
Optimiseur de renouvellements — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — Renewals 10 comptes · €89k ARR à 90j · 3 comptes at-risk · Playbook 6 scénarios. 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.
renewal_optimizer accepts 6 parameters: async, company, horizon, product, accounts, targetRenewalRatePct. Required: company, product, accounts. 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 renewal_optimizer: 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.
renewal_optimizer 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 renewal_optimizer 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 renewal_optimizer. 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.
renewal_optimizer 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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