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AI: orkestrasi

Orkestrasi AI mengikat ketiganya: mesin mendeteksi momen dalam status pengguna, memilih kohort, dan memilih tindakan, sehingga loop berjalan tanpa Anda menyambungkan tiap langkah secara manual.

At a glance

GraphQL
ai query: summarise, explain, suggest
MCP
Every prodantix.* tool, callable by an agent
MCP host
https://eu.mcp.prodantix.com
Auth
Access token
  • Mendeteksi momen yang bermakna dalam status langsung
  • Memilih kohort yang tepat dan tindakan yang tepat
  • Menutup loop: tindakan menjadi peristiwa berikutnya yang dipelajari mesin

Cara kerjanya

Every answer is grounded in rows the caller could already read. Citations are resolved server-side from a built candidate list rather than taken from the model’s reply, so an answer can only point at something that exists and the caller is entitled to see.

Di mana mengaksesnya

SurfaceOperation
GraphQLai query: summarise, explain, suggest
MCPevery prodantix.* tool, callable by an agent

Contoh

GraphQL
query Explain($projectId: String!) {
  ai {
    explainMetric(
      projectId: $projectId
      metric: "order.completed"
      window: "P7D"
    ) {
      summary
      citations { kind id }
    }
  }
}

Pointing an agent at prodantix

The MCP surface exposes the same capabilities to an autonomous agent. See MCP for the tool list and protocol details.

JSON
{
  "mcpServers": {
    "prodantix": {
      "url": "https://eu.mcp.prodantix.com/mcp",
      "headers": { "Authorization": "Bearer <access token>" }
    }
  }
}