Aggregate Promo Discounts (Messaging)

messagingmcp-aggregate_promos

Compute a statistic over promo discount depth, deduped by promo_id.

metric defaults to 'promo_depth' — the only aggregatable field — so it can be omitted. promo_depth_type is required (depths are unitless integers — without unit pinning the tool would mix percentages with currency amounts). Multi-buy promotions are EXCLUDED from every aggregate: their depth carries a third meaning (qualifying-item %, null for pure BOGO), so 'percentage' aggregates percentage_discount promos only and 'flat' aggregates flat_discount only. Returns a scalar value plus n_promos and n_observed (how many distinct promos contributed, and how many of those have a non-inferred row). With group_by or interval, returns a buckets array of those same shapes. group_by returns AT MOST 50 buckets — the groups with the most rows behind them — and the response does not say what it dropped: that is every group for 'promo_type', but a fraction of them for 'retailer' (hundreds even inside one region) and 'shoot' (many thousands). To ask about a particular retailer, filter to it rather than expecting it among the buckets.

Use for "average % off", "deepest discount", "median flat amount". For counts or row-level retrieval use count_promos / list_promos.

Parameters

Name	Type	Required	Constraints	Description
`statistic`	`string`	yes	—	Statistic to compute over distinct promotions' depth.
`promo_depth_type`	`string`	yes	—	REQUIRED. Pins the unit. 'percentage' for % off, 'flat' for currency-amount promos. Without it, percentages and currency amounts would be averaged together into a meaningless number.
`metric`	`string`	no	default: `"promo_depth"`	Field to aggregate. Only 'promo_depth' (numeric discount value) exists, so the param can be omitted.
`promo_currency`	`string`	no	—	ISO 4217 code (e.g. GBP, USD). REQUIRED when promo_depth_type='flat' — different currencies must not be averaged. Must be omitted for 'percentage' (rejected if supplied — percentages have no currency; use `regions` to scope a market).
`retailers`	`string[]`	no	—	Retailer slugs to filter by, e.g. ['zara', 'h-m']. Omit for all; matches any listed retailer. Slugs match exactly and are case-sensitive, so take them from `list_retailers`: match the request against `retailer_name`, then pass that row's `retailer` slug and one of the regions it reports.
`regions`	`string[]`	no	—	Regions to filter by, e.g. ['UK', 'US']. Omit for all; matches any listed region. Exact match, so use the values `list_retailers` reports for the retailer.
`start_date`	`string`	no	—	Inclusive start of the active-date window (YYYY-MM-DD).
`end_date`	`string`	no	—	Inclusive end of the active-date window (YYYY-MM-DD).
`min_depth`	`integer`	no	—	Minimum promo_depth. Depths are unitless — a percentage or a currency amount depending on the promo type — so constrain the type to avoid mixing units.
`max_depth`	`integer`	no	—	Maximum promo_depth. Same unit caveat as min_depth.
`has_code`	`boolean`	no	—	True = only promos with a code, False = only without; omit for no filter.
`include_inferred`	`boolean`	no	default: `true`	Include inferred promotions (default True). False = observed only.
`group_by`	`string`	no	—	Optional categorical bucketing. Mutually exclusive with `interval`. 'shoot' groups by source image to surface co-promoted bundles. Returns at most 50 buckets — the groups with the most rows behind them — and does not report what it omitted; 'retailer' and 'shoot' have far more groups than that, so treat the result as a top-50, not a complete set.
`interval`	`string`	no	—	Optional temporal bucketing on promotion_date. Exclusive with group_by. Rows are limited to [start_date, end_date], but bucket keys are calendar-aligned (week/month starts), so an edge bucket may be keyed before start_date and cover only the in-window part of its period.

Returns

On success: {"result": {"metric", "statistic", "promo_depth_type",
"promo_currency", "value", "n_promos", "n_observed", "filter_echo"}} —
the first four pin the unit the statistic is in, without which a depth is
meaningless.
With group_by or interval: {"result": {"metric", "statistic",
"promo_depth_type", "promo_currency", "buckets": [{group, value,
n_promos, n_observed}], "filter_echo"}}.
On failure: {"error": {code, message}}
code is invalid_input, upstream_unavailable, not_entitled
(authorization refused), or internal when the filtered set spans too
many distinct depths to describe in one pass — retry narrower, since
min_depth/max_depth, regions, retailers and promo_currency
each shrink that spread.

Try it

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Code examples

curl
TypeScript
Python

curl -s https://mcp.edited.com/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "MCP-Protocol-Version: 2025-06-18" \
  -H "x-api-key: $MCP_API_KEY" \
  -d '{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "messagingmcp-aggregate_promos",
    "arguments": {
      "statistic": "example",
      "promo_depth_type": "example",
      "metric": "promo_depth",
      "promo_currency": "example",
      "start_date": "example",
      "end_date": "example",
      "min_depth": 1,
      "max_depth": 1,
      "has_code": false,
      "include_inferred": true,
      "group_by": "example",
      "interval": "example"
    }
  }
}'

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";

const client = new Client({ name: "demo", version: "1.0.0" }, { capabilities: {} });
await client.connect(
  new StreamableHTTPClientTransport(new URL("https://mcp.edited.com/mcp"), {
    requestInit: { headers: { "x-api-key": process.env.MCP_API_KEY ?? "" } },
  }),
);

const result = await client.callTool({
  name: "messagingmcp-aggregate_promos",
  arguments: {
    "statistic": "example",
    "promo_depth_type": "example",
    "metric": "promo_depth",
    "promo_currency": "example",
    "start_date": "example",
    "end_date": "example",
    "min_depth": 1,
    "max_depth": 1,
    "has_code": false,
    "include_inferred": true,
    "group_by": "example",
    "interval": "example"
  },
});

import os
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

headers = {"x-api-key": os.environ["MCP_API_KEY"]}
async with streamablehttp_client("https://mcp.edited.com/mcp", headers=headers) as (read, write, _):
    async with ClientSession(read, write) as session:
        await session.initialize()
        result = await session.call_tool(
            "messagingmcp-aggregate_promos",
            {"statistic": "example", "promo_depth_type": "example", "metric": "promo_depth", "promo_currency": "example", "start_date": "example", "end_date": "example", "min_depth": 1, "max_depth": 1, "has_code": False, "include_inferred": True, "group_by": "example", "interval": "example"},
        )

Input schema

{
  "type": "object",
  "properties": {
    "statistic": {
      "description": "Statistic to compute over distinct promotions' depth.",
      "enum": [
        "mean",
        "median",
        "min",
        "max"
      ],
      "type": "string"
    },
    "promo_depth_type": {
      "description": "REQUIRED. Pins the unit. 'percentage' for % off, 'flat' for currency-amount promos. Without it, percentages and currency amounts would be averaged together into a meaningless number.",
      "enum": [
        "percentage",
        "flat"
      ],
      "type": "string"
    },
    "metric": {
      "const": "promo_depth",
      "default": "promo_depth",
      "description": "Field to aggregate. Only 'promo_depth' (numeric discount value) exists, so the param can be omitted.",
      "type": "string"
    },
    "promo_currency": {
      "description": "ISO 4217 code (e.g. GBP, USD). REQUIRED when promo_depth_type='flat' — different currencies must not be averaged. Must be omitted for 'percentage' (rejected if supplied — percentages have no currency; use `regions` to scope a market).",
      "type": "string"
    },
    "retailers": {
      "description": "Retailer slugs to filter by, e.g. ['zara', 'h-m']. Omit for all; matches any listed retailer. Slugs match exactly and are case-sensitive, so take them from `list_retailers`: match the request against `retailer_name`, then pass that row's `retailer` slug and one of the regions it reports.",
      "items": {
        "type": "string"
      },
      "type": "array"
    },
    "regions": {
      "description": "Regions to filter by, e.g. ['UK', 'US']. Omit for all; matches any listed region. Exact match, so use the values `list_retailers` reports for the retailer.",
      "items": {
        "type": "string"
      },
      "type": "array"
    },
    "start_date": {
      "description": "Inclusive start of the active-date window (YYYY-MM-DD).",
      "format": "date",
      "type": "string"
    },
    "end_date": {
      "description": "Inclusive end of the active-date window (YYYY-MM-DD).",
      "format": "date",
      "type": "string"
    },
    "min_depth": {
      "description": "Minimum promo_depth. Depths are unitless — a percentage or a currency amount depending on the promo type — so constrain the type to avoid mixing units.",
      "type": "integer"
    },
    "max_depth": {
      "description": "Maximum promo_depth. Same unit caveat as min_depth.",
      "type": "integer"
    },
    "has_code": {
      "description": "True = only promos with a code, False = only without; omit for no filter.",
      "type": "boolean"
    },
    "include_inferred": {
      "default": true,
      "description": "Include inferred promotions (default True). False = observed only.",
      "type": "boolean"
    },
    "group_by": {
      "description": "Optional categorical bucketing. Mutually exclusive with `interval`. 'shoot' groups by source image to surface co-promoted bundles. Returns at most 50 buckets — the groups with the most rows behind them — and does not report what it omitted; 'retailer' and 'shoot' have far more groups than that, so treat the result as a top-50, not a complete set.",
      "enum": [
        "retailer",
        "promo_type",
        "region",
        "shoot"
      ],
      "type": "string"
    },
    "interval": {
      "description": "Optional temporal bucketing on promotion_date. Exclusive with group_by. Rows are limited to [start_date, end_date], but bucket keys are calendar-aligned (week/month starts), so an edge bucket may be keyed before start_date and cover only the in-window part of its period.",
      "enum": [
        "day",
        "week",
        "month"
      ],
      "type": "string"
    }
  },
  "required": [
    "statistic",
    "promo_depth_type"
  ]
}

Output schema

Describes both branches of the envelope — result on success, error on a refusal. Validate against this rather than pattern-matching the prose above; see Concepts → Response shape.

{
  "type": "object",
  "properties": {
    "result": {
      "type": "object",
      "properties": {
        "value": {
          "anyOf": [
            {
              "type": "number"
            },
            {
              "type": "null"
            }
          ],
          "description": "Null when no matching promotion carried a depth."
        },
        "n_promos": {
          "description": "Distinct promotions, counted exactly to 40,000 and estimated above that (within roughly half a percent). Matched promotions carrying no depth are counted here but contribute nothing, so this sits above the population behind `value` by that share plus the estimate's error.",
          "type": "integer"
        },
        "n_observed": {
          "description": "Distinct promotions, counted exactly to 40,000 and estimated above that (within roughly half a percent). The subset with a directly-observed row.",
          "type": "integer"
        },
        "metric": {
          "const": "promo_depth",
          "type": "string"
        },
        "statistic": {
          "type": "string"
        },
        "promo_depth_type": {
          "type": "string"
        },
        "promo_currency": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ]
        },
        "filter_echo": {
          "properties": {
            "retailers": {
              "anyOf": [
                {
                  "items": {
                    "type": "string"
                  },
                  "type": "array"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "regions": {
              "anyOf": [
                {
                  "items": {
                    "type": "string"
                  },
                  "type": "array"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "start_date": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "end_date": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "include_inferred": {
              "anyOf": [
                {
                  "type": "boolean"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "min_depth": {
              "anyOf": [
                {
                  "type": "integer"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "max_depth": {
              "anyOf": [
                {
                  "type": "integer"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "has_code": {
              "anyOf": [
                {
                  "type": "boolean"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "statistic": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "promo_depth_type": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "promo_currency": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "group_by": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "interval": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            }
          },
          "type": "object"
        },
        "buckets": {
          "description": "Under group_by this is AT MOST 50 buckets — the groups with the most rows behind them, not the deepest — with no report of what was dropped; 50 buckets is a top-50, not a complete set.",
          "items": {
            "properties": {
              "value": {
                "anyOf": [
                  {
                    "type": "number"
                  },
                  {
                    "type": "null"
                  }
                ],
                "description": "Null when no matching promotion carried a depth."
              },
              "n_promos": {
                "description": "Distinct promotions, counted exactly to 40,000 and estimated above that (within roughly half a percent). Matched promotions carrying no depth are counted here but contribute nothing, so this sits above the population behind `value` by that share plus the estimate's error.",
                "type": "integer"
              },
              "n_observed": {
                "description": "Distinct promotions, counted exactly to 40,000 and estimated above that (within roughly half a percent). The subset with a directly-observed row.",
                "type": "integer"
              },
              "group": {
                "type": "string"
              }
            },
            "required": [
              "value",
              "n_promos",
              "n_observed",
              "group"
            ],
            "type": "object"
          },
          "type": "array"
        }
      },
      "required": [
        "filter_echo",
        "metric",
        "promo_currency",
        "promo_depth_type",
        "statistic"
      ],
      "allOf": [
        {
          "anyOf": [
            {
              "required": [
                "filter_echo",
                "metric",
                "n_observed",
                "n_promos",
                "promo_currency",
                "promo_depth_type",
                "statistic",
                "value"
              ]
            },
            {
              "required": [
                "buckets",
                "filter_echo",
                "metric",
                "promo_currency",
                "promo_depth_type",
                "statistic"
              ]
            }
          ]
        }
      ]
    },
    "error": {
      "type": "object",
      "description": "Present instead of `result` when the call was rejected. Branch on `code`; never string-match `message`.",
      "properties": {
        "code": {
          "type": "string",
          "enum": [
            "invalid_input",
            "not_entitled",
            "upstream_unavailable",
            "internal"
          ]
        },
        "message": {
          "type": "string"
        },
        "field": {
          "type": "string",
          "description": "Offending parameter, when the failure is attributable to one."
        },
        "details": {
          "type": "object",
          "additionalProperties": true
        }
      },
      "required": [
        "code",
        "message"
      ]
    }
  },
  "x-fastmcp-wrap-result": true,
  "oneOf": [
    {
      "required": [
        "result"
      ]
    },
    {
      "required": [
        "error"
      ]
    }
  ]
}

Parameters​

Returns​

Try it​

Code examples​

Input schema​

Output schema​