Tool Details: agent_info

Basic Information

Tool Name:agent_info
Asset Name:Agent Info
Description:Get a lightweight summary of an agent: status, config, capabilities, task count, timeline length, and any error. For more detail use covia_read: g/{agentId}/state/config (LLM settings, caps, context), g/{agentId}/state/history (conversation), g/{agentId}/timeline (run records), g/{agentId}/inbox (pending messages).
Adapter:agent
Asset Hash:0x6e74aee102e0aafea58e5f1ceed0af1b1be8a4f5873b9fd474e0ae17f64312e3
Input
PropertyTypeDescription
agentId*stringAgent name to query
Output
PropertyTypeDescription
tasksintegerNumber of pending tasks
errorstringLast error message, if suspended
statusstringSLEEPING, RUNNING, SUSPENDED, or TERMINATED
configobjectFramework config (operation, definition)
agentIdstring-
stateConfigobjectAgent's LLM config: model, systemPrompt, caps, context, responseFormat
timelineLengthintegerNumber of completed runs

MCP Tool Usage Examples

This tool can be called via the MCP (Model Context Protocol) endpoint. Here are examples of how to use it:

JSON-RPC Call Example:

POST to https://venue-3.covia.ai/mcp

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "agent_info",
    "arguments": {
      "input": "your input here"
    }
  }
}
cURL Example:
curl -X POST https://venue-3.covia.ai/mcp \\
  -H "Content-Type: application/json" \\
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "agent_info",
      "arguments": {
        "input": "your input here"
      }
    }
  }'
Python Example:
import requests
import json

url = "https://venue-3.covia.ai/mcp"
payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
        "name": "agent_info",
        "arguments": {
            "input": "your input here"
        }
    }
}

response = requests.post(url, json=payload)
result = response.json()
print(result)
JavaScript/Node.js Example:
const fetch = require('node-fetch');

const url = 'https://venue-3.covia.ai/mcp';
const payload = {
    jsonrpc: '2.0',
    id: 1,
    method: 'tools/call',
    params: {
        name: 'agent_info',
        arguments: {
            input: 'your input here'
        }
    }
};

fetch(url, {
    method: 'POST',
    headers: {
        'Content-Type': 'application/json'
    },
    body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data));

Asset Metadata

{
	"name": "Agent Info",
	"description": "Get a lightweight summary of an agent: status, config, capabilities, task count, timeline length, and any error. For more detail use covia_read: g/{agentId}/state/config (LLM settings, caps, context), g/{agentId}/state/history (conversation), g/{agentId}/timeline (run records), g/{agentId}/inbox (pending messages).",
	"dateCreated": "2026-04-01T00:00:00Z",
	"operation": {
		"adapter": "agent:info",
		"toolName": "agent_info",
		"input": {
			"type": "object",
			"properties": {
				"agentId": { "type": "string", "description": "Agent name to query" }
			},
			"required": ["agentId"]
		},
		"output": {
			"type": "object",
			"properties": {
				"agentId": { "type": "string" },
				"status": { "type": "string", "description": "SLEEPING, RUNNING, SUSPENDED, or TERMINATED" },
				"config": { "type": "object", "description": "Framework config (operation, definition)" },
				"stateConfig": { "type": "object", "description": "Agent's LLM config: model, systemPrompt, caps, context, responseFormat" },
				"timelineLength": { "type": "integer", "description": "Number of completed runs" },
				"tasks": { "type": "integer", "description": "Number of pending tasks" },
				"error": { "type": "string", "description": "Last error message, if suspended" }
			}
		}
	}
}

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