reputation_engine
Moteur de réputation — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: PayShield SaaS — Monitoring réputation Q2 2026. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/reputation-engine.md
What reputation_engine does on Mcp Knowledge
AI agents call reputation_engine 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 |
brand | string | Yes | |
channels | array | Yes | |
industry | string | Yes | |
keywords | array | Yes | |
historicalCrises | array | — |
Parameters from the server's own tool schema.
Why reputation_engine is rated Low
The tool appears to retrieve and return a structured reputation analysis/report (a read/query operation), analogous to a business intelligence or content metadata retrieval tool. However, the description is vague about side effects — 'agent-payable' hints at a financial transaction component (billing per use), and 'C-suite expertise' suggests it may trigger external analysis workflows.
From the tool's definition 'Moteur de réputation' (reputation engine), 'Returns a structured, audited deliverable', 'Monitoring réputation Q2 2026'
Attacks that exploit this kind of access
The rule that runs reputation_engine 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 reputation_engine, this is the rule to start with:
reputation_engine 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 reputation_engine call is checked against it from then on.
Questions about reputation_engine
Moteur de réputation — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Reference case: PayShield SaaS — Monitoring réputation Q2 2026. 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.
reputation_engine accepts 6 parameters: async, brand, channels, industry, keywords, historicalCrises. Required: brand, channels, industry, keywords. 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 reputation_engine: 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.
reputation_engine 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 reputation_engine 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 reputation_engine. 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.
reputation_engine 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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