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AI: orkestrasyon

Pinagdurugtong ng AI orchestration ang tatlo: tinutukoy ng engine ang sandali sa user state, pinipili ang cohort, at pinipili ang aksiyon, kaya tumatakbo ang loop nang hindi mo kinakailangang i-wire nang manual ang bawat hakbang.

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
  • Tinutukoy ang makabuluhang sandali sa live state
  • Pinipili ang tamang cohort at tamang aksiyon
  • Isinasara ang loop: ang aksiyon ay nagiging susunod na event na pinag-aaralan ng engine

Paano ito gumagana

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.

Saan ito maaabot

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

Halimbawa

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>" }
    }
  }
}