List all accessible Redmine saved queries. limit clamped to 1..100.
AI agents call list_queries to retrieve information from Redmine MCP OAuth Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only reads and returns a list of saved queries from Redmine. It has no side effects, does not modify data, does not execute arbitrary operations, and does not affect system state. The limit parameter clamping to 1..100 further confirms it is a simple list/pagination operation. This is a straightforward Read operation with low risk if accessed by an AI agent.
From the tool's definition Tool name is 'list_queries' and description states it 'List all accessible Redmine saved queries' — a purely retrieval operation with no modification, deletion, or execution of code.
Attacks that exploit this kind of access
List all accessible Redmine saved queries. limit clamped to 1..100. It is categorised as a Read tool in the Redmine MCP OAuth Server MCP Server, which means it retrieves data without modifying state.
Register the Redmine MCP OAuth Server MCP server in PolicyLayer and add a rule for list_queries: 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 Redmine MCP OAuth Server. Nothing to install.
list_queries 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 list_queries 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 list_queries. 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.
list_queries is provided by the Redmine MCP OAuth Server MCP server (zh/redmine_mcp_py). 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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