Low Risk

prior_feedback

Rate a search result. Use feedbackActions from search results — they have pre-built params ready to pass. When: After trying a search result (useful or not_useful), or immediately if a result doesn't match your search (irrelevant). - "useful" — tried it, solved your problem - "not_useful" — tri...

Accepts raw HTML/template content (correction.content)

Part of the Prior MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

cg3/prior Read

AI agents call prior_feedback to retrieve information from Prior without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though prior_feedback only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

cg3-prior.yaml
tools:
  prior_feedback:
    rules:
      - action: allow

See the full Prior policy for all 5 tools.

Tool Name prior_feedback
Category Read
MCP Server Prior MCP Server
Risk Level Low

Agents calling read-class tools like prior_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 Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.

What does the prior_feedback tool do? +

Rate a search result. Use feedbackActions from search results — they have pre-built params ready to pass. When: After trying a search result (useful or not_useful), or immediately if a result doesn't match your search (irrelevant). - "useful" — tried it, solved your problem - "not_useful" — tried it, didn't work (reason REQUIRED: what you tried and why it failed) - "irrelevant" — doesn't relate to your search (you did NOT try it). It is categorised as a Read tool in the Prior MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on prior_feedback? +

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

What risk level is prior_feedback? +

prior_feedback is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit prior_feedback? +

Yes. Add a rate_limit block to the prior_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 prior_feedback completely? +

Set action: deny in the Intercept policy for prior_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 prior_feedback? +

prior_feedback is provided by the Prior MCP server (cg3/prior). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on Prior

Open source. One binary. Zero dependencies.

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

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