Medium Risk

send_feedback

Report data quality issues for a business. Use when you notice incorrect phone numbers, wrong addresses, outdated info, or closed businesses.

Part of the discava – Business Directory for AI MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

discava/mcp-server Write Risk 2/5

AI agents use send_feedback to create or modify resources in discava – Business Directory for AI. 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 send_feedback repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach discava – Business Directory for AI.

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

discava-mcp-server.yaml
tools:
  send_feedback:
    rules:
      - action: allow
        rate_limit:
          max: 30
          window: 60

See the full discava – Business Directory for AI policy for all 6 tools.

Tool Name send_feedback
Category Write
Risk Level Medium

Agents calling write-class tools like send_feedback have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

What does the send_feedback tool do? +

Report data quality issues for a business. Use when you notice incorrect phone numbers, wrong addresses, outdated info, or closed businesses.. It is categorised as a Write tool in the discava – Business Directory for AI MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on send_feedback? +

Add a rule in your Intercept YAML policy under the tools section for send_feedback. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the discava – Business Directory for AI MCP server.

What risk level is send_feedback? +

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

Can I rate-limit send_feedback? +

Yes. Add a rate_limit block to the send_feedback rule in your Intercept 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 send_feedback completely? +

Set action: deny in the Intercept policy for send_feedback. 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 send_feedback? +

send_feedback is provided by the discava – Business Directory for AI MCP server (discava/mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on discava – Business Directory for AI

Open source. One binary. Zero dependencies.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
// GET IN TOUCH

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