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-4.covia.ai/mcp
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "agent_complete_task",
"arguments": {
"input": "your input here"
}
}
}
cURL Example:
curl -X POST https://venue-4.covia.ai/mcp \\
-H "Content-Type: application/json" \\
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "agent_complete_task",
"arguments": {
"input": "your input here"
}
}
}'
Python Example:
import requests
import json
url = "https://venue-4.covia.ai/mcp"
payload = {
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "agent_complete_task",
"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-4.covia.ai/mcp';
const payload = {
jsonrpc: '2.0',
id: 1,
method: 'tools/call',
params: {
name: 'agent_complete_task',
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": "Complete Agent Task",
"description": "Deliver the final result for the in-scope task and end it. This is terminal: the caller receives the result and nothing else. During an LLM transition, a long prose answer may be supplied as the message text with no result argument in the same turn; otherwise pass the answer in result. Only invoke this once the actual answer is ready. The agent and task are determined from the current request context — no id is passed. Without a task in scope the call fails. Side effects: completes the pending task Job and removes the task from the agent's task queue.",
"dateCreated": "2026-04-16T00:00:00Z",
"operation": {
"adapter": "agent:completeTask",
"toolName": "agent_complete_task",
"input": {
"type": "object",
"properties": {
"result": {
"description": "The result to deliver to the caller. Any JSON value is accepted. In an LLM transition it may be omitted only when the same turn's message text is the complete answer."
}
}
},
"output": {
"type": "object",
"properties": {
"agentId": { "type": "string" },
"taskId": { "type": "string" },
"status": { "type": "string", "description": "Always 'COMPLETE' on success." }
}
}
}
}