Conversation Ai Get Agent

Immutable Catalog Entry

This descriptor comes from the active versioned Portal catalog.

READghl.conversation_ai_get_agent

• Contract tier: agent_ready
• Risk: read
• Catalog version: 2026-07-12.2
• Descriptor hash: a8fa8c2e6cea068454b556a7f2b3912386d9e55c8b462c24f224d7c79eb1ab67

Get a GHL Conversation AI agent by ID. GHL category: AI Agents / Conversation AI. This is a read-only GHL Conversation AI operation. Agent personalities, goals, instructions, prompts, knowledge-base links, and action parameters are redacted by default; set includeFullConfig only when explicitly needed.

Request Body

{
  "jsonrpc": "2.0",
  "id": "ghl-conversation-ai-get-agent-example",
  "method": "tools/call",
  "params": {
    "name": "ghl.conversation_ai_get_agent",
    "arguments": {
      "agentId": "agentId_123",
      "query": {},
      "tenantId": "tenantId_123",
      "locationId": "locationId_123",
      "strictTenant": false,
      "includeFullConfig": false
    }
  }
}

Arguments Schema

{
  "type": "object",
  "required": [
    "agentId"
  ],
  "properties": {
    "query": {
      "type": "object",
      "description": "Optional GHL-supported query parameters for this official Conversation AI endpoint, such as pagination, agent, or generation filters from the official docs. Do not include locationId unless you only need local safety validation. For conversation_ai_search_agents, search/q/name are accepted but applied locally because GHL rejects those query fields.",
      "additionalProperties": true
    },
    "agentId": {
      "type": "string",
      "description": "agentId path parameter required by /conversation-ai/agents/:agentId."
    },
    "tenantId": {
      "type": "string",
      "description": "Tenant ID from list_tenants."
    },
    "locationId": {
      "type": "string",
      "description": "Optional GHL location ID for safety validation only. If provided, it must match the authenticated runtime location; Conversation AI endpoints are scoped by the PIT token and this field is not forwarded to GHL."
    },
    "strictTenant": {
      "type": "boolean",
      "default": true,
      "description": "Require tenantId to match locationId routing (default: true)."
    },
    "includeFullConfig": {
      "type": "boolean",
      "description": "Defaults to false. Set true only when the user explicitly needs full Conversation AI configuration such as personality, goal, instructions, prompts, knowledge-base IDs, or action parameters."
    }
  },
  "additionalProperties": false
}

Output Schema

{
  "type": "object",
  "required": [
    "ok",
    "data",
    "error",
    "meta"
  ],
  "properties": {
    "ok": {
      "type": "boolean",
      "description": "Whether the GHL MCP operation completed successfully."
    },
    "data": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "array",
          "items": {}
        },
        {
          "type": "string"
        },
        {
          "type": "number"
        },
        {
          "type": "boolean"
        },
        {
          "type": "null"
        }
      ],
      "description": "Tool-specific GHL or local navigation result when ok is true."
    },
    "meta": {
      "type": "object",
      "description": "Safe execution, routing, and timing metadata.",
      "additionalProperties": true
    },
    "error": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "null"
        }
      ],
      "description": "Safe error details when ok is false; credential values are never returned."
    }
  },
  "description": "Normalized GHL MCP response envelope.",
  "additionalProperties": false
}

Code Examples

cURL

curl -X POST 'https://portal.madpanda3d.com/api/mcp' \
  -H 'Authorization: Bearer mad_live_***' \
  -H 'Content-Type: application/json' \
  -d '{
  "jsonrpc": "2.0",
  "id": "ghl-conversation-ai-get-agent-example",
  "method": "tools/call",
  "params": {
    "name": "ghl.conversation_ai_get_agent",
    "arguments": {
      "agentId": "agentId_123",
      "query": {},
      "tenantId": "tenantId_123",
      "locationId": "locationId_123",
      "strictTenant": false,
      "includeFullConfig": false
    }
  }
}'

Node.js

const response = await fetch('https://portal.madpanda3d.com/api/mcp', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer mad_live_***',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
  "jsonrpc": "2.0",
  "id": "ghl-conversation-ai-get-agent-example",
  "method": "tools/call",
  "params": {
    "name": "ghl.conversation_ai_get_agent",
    "arguments": {
      "agentId": "agentId_123",
      "query": {},
      "tenantId": "tenantId_123",
      "locationId": "locationId_123",
      "strictTenant": false,
      "includeFullConfig": false
    }
  }
}),
});
const data = await response.json();
console.log(data);

Python

import requests

url = 'https://portal.madpanda3d.com/api/mcp'
headers = {
    'Authorization': 'Bearer mad_live_***',
    'Content-Type': 'application/json',
}
payload = {
  "jsonrpc": "2.0",
  "id": "ghl-conversation-ai-get-agent-example",
  "method": "tools/call",
  "params": {
    "name": "ghl.conversation_ai_get_agent",
    "arguments": {
      "agentId": "agentId_123",
      "query": {},
      "tenantId": "tenantId_123",
      "locationId": "locationId_123",
      "strictTenant": false,
      "includeFullConfig": false
    }
  }
}
response = requests.post(url, headers=headers, json=payload, timeout=60)
print(response.json())

Example Responses

200 Success

{
  "ok": true,
  "message": "Tool ghl.conversation_ai_get_agent executed successfully.",
  "note": "Response shape varies by MCP tool. Inspect live responses for exact fields."
}

502 Upstream Error

{
  "ok": false,
  "classification": "upstream_http_error",
  "message": "Upstream MCP returned a non-success status."
}