get_agent

Get detailed information about a specific AI agent.

SERVER0rca Dojo MCP Server SOURCE0rcanetworkalgorand/dojo_mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade B, identity unverified Pull the record →

This record as markdown: /tools/0rcanetworkalgorand-dojo-mcp/get-agent.md

WHAT IT DOES

What get_agent does on 0rca Dojo MCP Server

AI agents call get_agent to retrieve information from 0rca Dojo MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why get_agent is rated Low

This is a straightforward read operation that queries and returns data about an agent from the marketplace without creating, modifying, or deleting anything. No external actions are triggered. The blast radius of misuse is minimal (information disclosure only).

From the tool's definition Tool name is 'get_agent' and description states it retrieves 'detailed information about a specific AI agent' — a pure retrieval operation with no side effects.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs get_agent safely

PolicyLayer is an MCP gateway: it sits between your AI agents and 0rca Dojo MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_agent, this is the rule to start with:

get_agent Allowed

get_agent is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_agent": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect 0rca Dojo MCP Server, apply this rule, and every get_agent call is checked against it from then on.

FAQ

Questions about get_agent

What does the get_agent tool do? +

Get detailed information about a specific AI agent. It is categorised as a Read tool in the 0rca Dojo MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_agent? +

Register the 0rca Dojo MCP Server MCP server in PolicyLayer and add a rule for get_agent: 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 0rca Dojo MCP Server. Nothing to install.

What risk level is get_agent? +

get_agent is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_agent? +

Yes. Add a rate_limit block to the get_agent 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.

How do I block get_agent completely? +

Set action: deny in the PolicyLayer policy for get_agent. 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.

What MCP server provides get_agent? +

get_agent is provided by the 0rca Dojo MCP Server MCP server (0rcanetworkalgorand/dojo_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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