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
aiquery: 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
| Surface | Operation |
|---|---|
| GraphQL | ai query: summarise, explain, suggest |
| MCP | every 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>" }
}
}
}