AI agents invoke query to trigger actions in Highgo. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
The tool executes arbitrary SQL on a database, supporting both read queries and modification operations. Since it allows arbitrary SQL execution including potentially destructive statements (DROP, DELETE, TRUNCATE) and data modifications, it spans Execute and Destructive categories.
From the tool's definition "执行 SQL 查询" (execute SQL queries), "支持查询和修改操作" (supports query and modification operations)
Attacks that exploit this kind of access
在瀚高数据库上执行 SQL 查询。支持查询和修改操作。可以使用 search_path 切换 schema。. It is categorised as a Execute tool in the Highgo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Highgo MCP server in PolicyLayer and add a rule for query: 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 Highgo. Nothing to install.
query is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the query 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 query. 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.
query is provided by the Highgo MCP server (otaku-wang/highgo-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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