AI agents call rag_list_projects to retrieve information from Ragi without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves or enumerates existing projects and validates paths—purely informational operations with no side effects, no code execution, and no data modification. It is a straightforward Read operation with minimal security risk.
From the tool's definition Tool name 'rag_list_projects' and description 'List available projects or validate a project path' indicate a retrieval/query operation with no data modification or execution.
Attacks that exploit this kind of access
List available projects or validate a project path. It is categorised as a Read tool in the Ragi MCP Server, which means it retrieves data without modifying state.
Register the Ragi MCP server in PolicyLayer and add a rule for rag_list_projects: 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 Ragi. Nothing to install.
rag_list_projects 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 rag_list_projects 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 rag_list_projects. 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.
rag_list_projects is provided by the Ragi MCP server (susutawar/ragi). 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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