churn_defender
Bouclier anti-churn — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Spendesk — portefeuille 400 clients PME/ETI, détection churn Q2 2025 (€8M ARR). Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/churn-defender.md
What churn_defender does on Mcp Knowledge
AI agents call churn_defender 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 |
company | object | Yes | |
accounts | array | Yes | |
csrContext | string | — | |
analysisWindowDays | integer | Yes |
Parameters from the server's own tool schema.
Why churn_defender is rated Low
The tool appears to perform churn analysis and detection, returning a structured report/deliverable. This is primarily a Read/analysis operation — querying and analyzing customer data to identify churn risk. The reference to a C-suite CRO expertise deliverable suggests it synthesizes and returns analytical output rather than modifying data.
From the tool's definition 'Bouclier anti-churn' (churn shield), 'Returns a structured, audited deliverable', 'détection churn' (churn detection)
Risk signalsHigh parameter count (28 properties)
Attacks that exploit this kind of access
The rule that runs churn_defender 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 churn_defender, this is the rule to start with:
churn_defender 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 churn_defender call is checked against it from then on.
Questions about churn_defender
Bouclier anti-churn — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Spendesk — portefeuille 400 clients PME/ETI, détection churn Q2 2025 (€8M 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.
churn_defender accepts 5 parameters: async, company, accounts, csrContext, analysisWindowDays. Required: company, accounts, analysisWindowDays. 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 churn_defender: 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.
churn_defender 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 churn_defender 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 churn_defender. 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.
churn_defender 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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