Historical record of goals the user hit — one row per (goal, day). Each row carries a snapshot of the goal as it was when achieved (so renamed/deleted goals still report sensibly). Useful for streak questions (
AI agents call get_goal_achievements to retrieve information from Vetroscope MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries historical goal achievement data without side effects. The read-only server constraint and the retrieval-only nature of the operation (returning snapshots of past goals for analysis) confirm it belongs in the Read category. Severity is low because access to personal time-tracking history poses minimal risk of harm if misused by an AI agent.
From the tool's definition Tool name 'get_goal_achievements' and description explicitly state it retrieves 'historical record' of goals; server description emphasizes 'read-only' access to time-tracking data from local SQLite database.
Attacks that exploit this kind of access
Historical record of goals the user hit — one row per (goal, day). Each row carries a snapshot of the goal as it was when achieved (so renamed/deleted goals still report sensibly). Useful for streak questions (. It is categorised as a Read tool in the Vetroscope MCP MCP Server, which means it retrieves data without modifying state.
Register the Vetroscope MCP server in PolicyLayer and add a rule for get_goal_achievements: 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 Vetroscope MCP. Nothing to install.
get_goal_achievements 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 get_goal_achievements 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 get_goal_achievements. 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.
get_goal_achievements is provided by the Vetroscope MCP server (rankin-works/vetroscope-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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