Retivo

MCP Integration

Connect Retivo to AI assistants via the Model Context Protocol

The Model Context Protocol (MCP) lets AI assistants like Claude, ChatGPT, and custom agents interact with Retivo using a standard JSON-RPC 2.0 interface.

Use Cases

Why connect an AI assistant to Retivo?

  • Customer support agents — AI agents can check user status and trigger targeted interventions during support conversations
  • Sales copilots — Surface activation scores and risk levels to help sales reps prioritize outreach
  • Internal tools — Build custom AI workflows that react to user lifecycle changes

Endpoint

POST /api/mcp
Authorization: Bearer rt_live_...
Content-Type: application/json

All requests use the JSON-RPC 2.0 format:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "tool_name",
    "arguments": { ... }
  }
}

Available Tools

track_event

Track a user event from an AI workflow.

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "track_event",
    "arguments": {
      "user_id": "user-123",
      "event_name": "ai_task_completed",
      "properties": { "task": "sprint_planning" }
    }
  }
}

Response:

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "content": [{ "type": "text", "text": "Event \"ai_task_completed\" tracked for user user-123" }]
  }
}

get_user_status

Get a user's lifecycle stage, health score, and risk level.

{
  "params": {
    "name": "get_user_status",
    "arguments": { "user_id": "user-123" }
  }
}

Returns lifecycle stage, activation score, risk level, last activity, opt-out and pause status.

get_recommendations

Get AI-recommended actions for a specific user.

{
  "params": {
    "name": "get_recommendations",
    "arguments": { "user_id": "user-123" }
  }
}

Runs the full AI evaluation pipeline for a user, returning a structured recommendation with action, playbook, channel, confidence score, and reasoning.

Response:

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "content": [{
      "type": "text",
      "text": "{\"action\":\"intervene\",\"playbook\":\"Onboarding Kickstart\",\"channel\":\"email\",\"confidence\":0.82,\"reasoning\":\"User hasn't completed onboarding in 5 days\"}"
    }]
  }
}

trigger_intervention

Manually trigger an intervention for a user through a specific channel.

{
  "params": {
    "name": "trigger_intervention",
    "arguments": {
      "user_id": "user-123",
      "playbook_id": "pb_abc",
      "channel": "email"
    }
  }
}

Channels: email, in_app, webhook

pause_user

Pause all interventions for a user.

{
  "params": {
    "name": "pause_user",
    "arguments": {
      "user_id": "user-123",
      "reason": "User requested quiet period"
    }
  }
}

list_playbooks

List all active playbooks for your tenant.

{
  "params": {
    "name": "list_playbooks",
    "arguments": {}
  }
}

Discovering Tools

To list all available tools programmatically:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Returns tool names, descriptions, and input schemas — compatible with the MCP tool discovery spec.

Error Handling

Errors follow the JSON-RPC 2.0 error format:

{
  "jsonrpc": "2.0",
  "id": 1,
  "error": {
    "code": -32601,
    "message": "Unknown tool: invalid_tool"
  }
}
CodeMeaning
-32600Invalid JSON-RPC request
-32601Unknown method or tool

Example: Claude Desktop Integration

Add Retivo to your Claude Desktop MCP config:

{
  "mcpServers": {
    "retivo": {
      "url": "https://retivo.ai/api/mcp",
      "headers": {
        "Authorization": "Bearer rt_live_..."
      }
    }
  }
}

Once connected, Claude can track events, check user status, and trigger interventions on your behalf through natural language.

Example: Cursor Integration

Add to .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "retivo": {
      "url": "https://retivo.ai/api/mcp",
      "headers": {
        "Authorization": "Bearer rt_live_..."
      }
    }
  }
}

Example: VS Code (Copilot) Integration

Add to .vscode/settings.json:

{
  "mcp": {
    "servers": {
      "retivo": {
        "type": "http",
        "url": "https://retivo.ai/api/mcp",
        "headers": {
          "Authorization": "Bearer rt_live_..."
        }
      }
    }
  }
}

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