sales_enablement_architect
Architecte Sales Enablement — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Spendesk — 45 reps · attainment 67% · ramp 5 mois → 3 mois · programme 8 modules · +€2,1M ARR. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/sales-enablement-architect.md
What sales_enablement_architect does on Mcp Knowledge
AI agents call sales_enablement_architect 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 |
|---|---|---|---|
gaps | array | Yes | |
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 | |
salesTeam | object | Yes | |
objectives | array | Yes | |
currentEnablement | object | Yes |
Parameters from the server's own tool schema.
Why sales_enablement_architect is rated Low
The tool appears to return structured advisory content (a sales enablement plan/deliverable) based on input case fields. It is framed as an expert analysis engine that produces a document/report, not one that modifies data, executes code, or moves money. The reference case (Spendesk) is illustrative output, not a side effect.
From the tool's definition 'Architecte Sales Enablement' returning 'a structured, audited deliverable' and 'C-suite expertise (CRO)' — the tool generates analysis/recommendations based on input fields
Risk signalsHigh parameter count (28 properties)
Attacks that exploit this kind of access
The rule that runs sales_enablement_architect 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 sales_enablement_architect, this is the rule to start with:
sales_enablement_architect 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 sales_enablement_architect call is checked against it from then on.
Questions about sales_enablement_architect
Architecte Sales Enablement — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Spendesk — 45 reps · attainment 67% · ramp 5 mois → 3 mois · programme 8 modules · +€2,1M ARR. 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.
sales_enablement_architect accepts 6 parameters: gaps, async, company, salesTeam, objectives, currentEnablement. Required: gaps, company, salesTeam, objectives, currentEnablement. 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 sales_enablement_architect: 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.
sales_enablement_architect 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 sales_enablement_architect 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 sales_enablement_architect. 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.
sales_enablement_architect 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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