Medium Risk

ma_deal_screener

M&A Deal Screener — Gapup agent-payable C-suite expertise (CSO). Returns a structured, audited deliverable. Reference case: Salesforce M&A targets — 12 cibles screened · fit score + valuation + integration risk. Inputs are validated server-side — send the documented case fields.

Risk signalsHigh parameter count (12 properties)

Part of the Mcp Knowledge server.

ma_deal_screener can modify Mcp Knowledge data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use ma_deal_screener to create or modify resources in Mcp Knowledge. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call ma_deal_screener repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mcp Knowledge.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "ma_deal_screener": {
      "limits": [
        {
          "counter": "ma_deal_screener_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access ma_deal_screener gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so ma_deal_screener only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the ma_deal_screener tool do? +

M&A Deal Screener — Gapup agent-payable C-suite expertise (CSO). Returns a structured, audited deliverable. Reference case: Salesforce M&A targets — 12 cibles screened · fit score + valuation + integration risk. Inputs are validated server-side — send the documented case fields.. It is categorised as a Write tool in the Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on ma_deal_screener? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for ma_deal_screener: 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.

What risk level is ma_deal_screener? +

ma_deal_screener is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit ma_deal_screener? +

Yes. Add a rate_limit block to the ma_deal_screener 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.

How do I block ma_deal_screener completely? +

Set action: deny in the PolicyLayer policy for ma_deal_screener. 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.

What MCP server provides ma_deal_screener? +

ma_deal_screener 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.

Enforce policy on every Mcp Knowledge tool call.

Deterministic rules across all 271 Mcp Knowledge tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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