discovery_prep
Préparation discovery — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Discovery Salesforce × Airbus — VP Digital Marc Legrand · Signaux achat confirmés · +28 pts conversion demo. Inputs are validated server-side — send the documented case ...
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/discovery-prep.md
What discovery_prep does on Mcp Knowledge
AI agents call discovery_prep 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 |
contact | object | Yes | |
ourOffer | string | Yes | |
prospect | object | Yes | |
meetingGoal | string | — |
Parameters from the server's own tool schema.
Why discovery_prep is rated Low
The tool appears to prepare and return structured discovery/sales intelligence content (reading and analyzing data about a prospect or case). It does not appear to write, execute, delete, or involve financial transactions. The description is partially marketing-oriented and light on technical detail, which lowers confidence.
From the tool's definition Préparation discovery — returns a structured, audited deliverable. Reference case mentions conversion demo analysis and buy signals.
Risk signalsAccepts URL/endpoint input (prospect.url) · High parameter count (11 properties)
Attacks that exploit this kind of access
The rule that runs discovery_prep 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 discovery_prep, this is the rule to start with:
discovery_prep 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 discovery_prep call is checked against it from then on.
Questions about discovery_prep
Préparation discovery — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Discovery Salesforce × Airbus — VP Digital Marc Legrand · Signaux achat confirmés · +28 pts conversion demo. 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.
discovery_prep accepts 5 parameters: async, contact, ourOffer, prospect, meetingGoal. Required: contact, ourOffer, prospect. 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 discovery_prep: 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.
discovery_prep 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 discovery_prep 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 discovery_prep. 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.
discovery_prep 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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