Search and filter customer feedback in a LaunchNotes project. Args: - project_id (string): The ID of the project (required) - query (string, optional): Search term to find in feedback content - reaction (
AI agents call launchnotes_search_feedback to retrieve information from LaunchNotes MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries feedback data without creating, modifying, or deleting any content. It is a straightforward search/filter operation that returns data with no side effects, fitting the Read category. Severity is low because feedback retrieval has minimal business impact even if misused.
From the tool's definition Tool name includes 'search' and description states 'Search and filter customer feedback' with no mention of modifications, deletions, or side effects. Arguments include 'project_id' and optional 'query' parameters typical of read operations.
Attacks that exploit this kind of access
Search and filter customer feedback in a LaunchNotes project. Args: - project_id (string): The ID of the project (required) - query (string, optional): Search term to find in feedback content - reaction (. It is categorised as a Read tool in the LaunchNotes MCP Server MCP Server, which means it retrieves data without modifying state.
Register the LaunchNotes MCP Server MCP server in PolicyLayer and add a rule for launchnotes_search_feedback: 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 LaunchNotes MCP Server. Nothing to install.
launchnotes_search_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 launchnotes_search_feedback 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 launchnotes_search_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.
launchnotes_search_feedback is provided by the LaunchNotes MCP Server MCP server (launchnotes/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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