Lists available Dingo rule groups, registered LLM model identifiers, and prompt definitions. Ensures all models are loaded before retrieving the lists. If include_details is True, will attempt to provide more metadata. Args: component_type: Type of components to list ('rule_groups', 'llm_models',...
AI agents call list_dingo_components to retrieve information from Dingo MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This is a pure read/query operation that retrieves and enumerates configuration metadata from the Dingo system. The include_details parameter only controls the verbosity of returned information, not any side effects. There is no code execution, data modification, deletion, or financial impact. Low severity because listing available components poses minimal risk even if an AI agent calls it without intent.
From the tool's definition Tool 'lists available Dingo rule groups, registered LLM model identifiers, and prompt definitions' with args to control what is listed and whether to include details. Returns dictionaries of components.
Documented attack patterns abuse exactly the kind of access list_dingo_components gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Dingo MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for list_dingo_components:
{
"version": "1",
"default": "deny",
"tools": {
"list_dingo_components": {}
}
}list_dingo_components is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Lists available Dingo rule groups, registered LLM model identifiers, and prompt definitions. Ensures all models are loaded before retrieving the lists. If include_details is True, will attempt to provide more metadata. Args: component_type: Type of components to list ('rule_groups', 'llm_models', 'prompts', or 'all'). include_details: Whether to include detailed descriptions and metadata for each component. Returns: A dictionary containing 'rule_groups', 'llm_models', 'prompts', and/or 'llm_prompt_mappings' based on component_type. It is categorised as a Read tool in the Dingo MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Dingo MCP Server MCP server in PolicyLayer and add a rule for list_dingo_components: 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 Dingo MCP Server. Nothing to install.
list_dingo_components 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_dingo_components 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_dingo_components. 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_dingo_components is provided by the Dingo MCP Server MCP server (migoxlab/dingo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Dingo MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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6 Dingo MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.