cross_sell_reco
Recommandations cross-sell — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Alan × Gapup Hub — 3 produits recommandés · Fit 'perfect' × 2 · ARR potentiel +€18k. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/cross-sell-reco.md
What cross_sell_reco does on Mcp Knowledge
AI agents call cross_sell_reco 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 |
account | object | Yes | |
company | object | Yes | |
portfolio | array | Yes |
Parameters from the server's own tool schema.
Why cross_sell_reco is rated Low
The tool generates cross-sell recommendations and returns a structured analytical deliverable. It reads/analyzes inputs and produces advisory output (product recommendations with fit scores and ARR potential). There is no indication it executes transactions, modifies data, or commits financial obligations — it provides intelligence/recommendations only, similar to a query or analysis tool.
From the tool's definition Recommandations cross-sell — Returns a structured, audited deliverable. Reference case: Alan × Gapup Hub — 3 produits recommandés · Fit 'perfect' × 2 · ARR potentiel +€18k.
Risk signalsHigh parameter count (13 properties)
Attacks that exploit this kind of access
The rule that runs cross_sell_reco 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 cross_sell_reco, this is the rule to start with:
cross_sell_reco 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 cross_sell_reco call is checked against it from then on.
Questions about cross_sell_reco
Recommandations cross-sell — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Alan × Gapup Hub — 3 produits recommandés · Fit 'perfect' × 2 · ARR potentiel +€18k. 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.
cross_sell_reco accepts 4 parameters: async, account, company, portfolio. Required: account, company, portfolio. 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 cross_sell_reco: 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.
cross_sell_reco 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 cross_sell_reco 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 cross_sell_reco. 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.
cross_sell_reco 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.
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