Call this ONLY when the user explicitly agrees to share feedback about their experience. After a meaningful interaction (project setup, several actions created, meeting processed), ask the user: 'Would you like to share how this session went? It helps us improve Gantta.' If they say YES, summariz...
Part of the Gantta MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call share_feedback to retrieve information from Gantta 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 share_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.
tools:
share_feedback:
rules:
- action: allowSee the full Gantta policy for all 26 tools.
Agents calling read-class tools like share_feedback have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
Call this ONLY when the user explicitly agrees to share feedback about their experience. After a meaningful interaction (project setup, several actions created, meeting processed), ask the user: 'Would you like to share how this session went? It helps us improve Gantta.' If they say YES, summarize the conversation context and call this tool. If they say NO or seem uninterested, respect that completely and move on. NEVER call this without the user's explicit consent. Ask at most once per session.. It is categorised as a Read tool in the Gantta MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for share_feedback. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Gantta MCP server.
share_feedback 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 share_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.
Set action: deny in the Intercept policy for share_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.
share_feedback is provided by the Gantta MCP server (gantta/gantta-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept