meddic_scoring
Scoring MEDDIC du pipeline — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — Pipeline 8 deals · €2.1M · MEDDIC score moyen 62/100 · 3 deals at-risk. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/meddic-scoring.md
What meddic_scoring does on Mcp Knowledge
AI agents call meddic_scoring 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 |
deals | array | Yes | |
company | object | Yes | |
product | object | Yes | |
salesCycle | object | — | |
targetWinRate | number | — |
Parameters from the server's own tool schema.
Why meddic_scoring is rated Low
The tool appears to analyze and score sales pipeline deals using the MEDDIC framework, returning a structured report. This is fundamentally a read/analysis operation with no evident side effects. Severity is low because misuse would at worst produce incorrect scoring output.
From the tool's definition 'Scoring MEDDIC du pipeline' — scores/audits pipeline deals and 'Returns a structured, audited deliverable'; no mention of creating, modifying, deleting, or executing anything
Risk signalsHigh parameter count (25 properties)
Attacks that exploit this kind of access
The rule that runs meddic_scoring 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 meddic_scoring, this is the rule to start with:
meddic_scoring 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 meddic_scoring call is checked against it from then on.
Questions about meddic_scoring
Scoring MEDDIC du pipeline — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub — Pipeline 8 deals · €2.1M · MEDDIC score moyen 62/100 · 3 deals at-risk. 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.
meddic_scoring accepts 6 parameters: async, deals, company, product, salesCycle, targetWinRate. Required: deals, company, product. 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 meddic_scoring: 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.
meddic_scoring 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 meddic_scoring 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 meddic_scoring. 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.
meddic_scoring 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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