AI agents call get_saiketsu to retrieve information from Tax Law without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves official Japanese tax law precedent data from a local server without creating, modifying, or deleting any information. It is a straightforward information lookup function comparable to a database query that returns static legal document content.
From the tool's definition Tool name 'get_saiketsu' and description indicate it retrieves full text of tax tribunal precedent cases (国税不服審判所の裁決事例の全文を取得する) by URL or case collection number.
Attacks that exploit this kind of access
国税不服審判所の裁決事例の全文を取得する。URLまたは事例集番号+事例番号で指定。search_saiketsuの検索結果から全文を読む場合に使用。. It is categorised as a Read tool in the Tax Law MCP Server, which means it retrieves data without modifying state.
Register the Tax Law MCP server in PolicyLayer and add a rule for get_saiketsu: 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 Tax Law. Nothing to install.
get_saiketsu 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_saiketsu 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_saiketsu. 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_saiketsu is provided by the Tax Law MCP server (xqzimgz/tax-law-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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