lead_magnets
Aimants à leads — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Spendesk — Guide trésorerie startup SaaS B2B FR/EU (2024). Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/lead-magnets.md
What lead_magnets does on Mcp Knowledge
AI agents call lead_magnets 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 |
|---|---|---|---|
icp | object | 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 |
brand | object | Yes | |
leadMagnet | object | Yes |
Parameters from the server's own tool schema.
Why lead_magnets is rated Low
The tool description focuses on returning a structured deliverable (a lead magnet guide), which is primarily a content generation/retrieval operation. It references a CMO-level expertise output and a documented reference case. There is no indication of writes, deletions, code execution, or financial transactions. The description is partially in French and somewhat vague, which reduces confidence slightly.
From the tool's definition 'Returns a structured, audited deliverable' and 'Guide trésorerie startup SaaS B2B FR/EU (2024)' — the tool appears to generate/return a lead magnet content document based on inputs
Risk signalsHigh parameter count (16 properties)
Attacks that exploit this kind of access
The rule that runs lead_magnets 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 lead_magnets, this is the rule to start with:
lead_magnets 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 lead_magnets call is checked against it from then on.
Questions about lead_magnets
Aimants à leads — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: Spendesk — Guide trésorerie startup SaaS B2B FR/EU (2024). 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.
lead_magnets accepts 4 parameters: icp, async, brand, leadMagnet. Required: icp, brand, leadMagnet. 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 lead_magnets: 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.
lead_magnets 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 lead_magnets 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 lead_magnets. 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.
lead_magnets 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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