Search Promo Text (Messaging)
messagingmcp-search_promo_text
Relevance-scored text search across promo description / conditions / categories / codes.
The searched text is plain English (extraction translates all source
languages), and the corpus targets quantified-discount promotions — free
shipping, loyalty perks, and single-product sales are excluded by policy, so
searching for them is unreliable (compound offers like "20% off plus free
shipping" do match; a few stray pure records exist); see
explain_promo_data. Returns one entry per distinct
promotion (highest-scoring row per promo), each with the list_promos field
set plus active_window, any_inferred, and a raw BM25 score (ordering
only — not a probability). total_matched and coverage mirror list_promos.
Double-quote a span to match it as an exact phrase ("40% off"); quotes can be
mixed with loose terms and repeated, but everything is OR-combined — a hit
needs only one of the phrases/terms, so a mixed query does NOT require the
phrase. To require a phrase, send it alone. Phrasing matches adjacent words,
not literal punctuation. categories is a keyword field — it only matches a
whole value exactly, not individual words.
Parameters
| Name | Type | Required | Constraints | Description |
|---|---|---|---|---|
query | string | yes | — | Keyword or short phrase to match across promo text. Lean, specific terms work best — the corpus is already filtered to promos so generic words match everything. Wrap a span in double quotes to match it as an exact phrase, e.g. "40% off" — quotes can be mixed with loose terms and repeated, e.g. "buy one get one" student. Phrasing matches adjacent words, not literal punctuation (a % is not indexed). |
fields | string[] | no | — | Which text fields to search. Subset of ['description', 'conditions', 'categories', 'codes']. Omit for all four (description and codes boosted). |
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 | — | Start of the active-date window (inclusive, YYYY-MM-DD). |
end_date | string | no | — | End of the active-date window (inclusive, YYYY-MM-DD). |
include_inferred | boolean | no | default: true | Include inferred promotions (default True). False = observed only. |
limit | integer | no | default: 10 · 1–20 | Max distinct promotions. |
Returns
- On success: {"result": {"total_matched", "coverage", "returned",
- "promos": [...], "filter_echo"}}.
- On failure: {"error": {code, message}}
codeisinvalid_input,upstream_unavailable, ornot_entitled(authorization refused).
Try it
Loading interactive widget…
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-search_promo_text",
"arguments": {
"query": "Nike",
"start_date": "example",
"end_date": "example",
"include_inferred": true,
"limit": 10
}
}
}'
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-search_promo_text",
arguments: {
"query": "Nike",
"start_date": "example",
"end_date": "example",
"include_inferred": true,
"limit": 10
},
});
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-search_promo_text",
{"query": "Nike", "start_date": "example", "end_date": "example", "include_inferred": True, "limit": 10},
)
Input schema
{
"type": "object",
"properties": {
"query": {
"description": "Keyword or short phrase to match across promo text. Lean, specific terms work best — the corpus is already filtered to promos so generic words match everything. Wrap a span in double quotes to match it as an exact phrase, e.g. \"40% off\" — quotes can be mixed with loose terms and repeated, e.g. \"buy one get one\" student. Phrasing matches adjacent words, not literal punctuation (a `%` is not indexed).",
"type": "string"
},
"fields": {
"description": "Which text fields to search. Subset of ['description', 'conditions', 'categories', 'codes']. Omit for all four (description and codes boosted).",
"items": {
"type": "string"
},
"type": "array"
},
"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": "Start of the active-date window (inclusive, YYYY-MM-DD).",
"format": "date",
"type": "string"
},
"end_date": {
"description": "End of the active-date window (inclusive, YYYY-MM-DD).",
"format": "date",
"type": "string"
},
"include_inferred": {
"default": true,
"description": "Include inferred promotions (default True). False = observed only.",
"type": "boolean"
},
"limit": {
"default": 10,
"description": "Max distinct promotions.",
"maximum": 20,
"minimum": 1,
"type": "integer"
}
},
"required": [
"query"
]
}
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": {
"properties": {
"total_matched": {
"description": "Distinct promotions, counted exactly to 40,000 and estimated above that (within roughly half a percent). The full count; the page in promos may be smaller.",
"type": "integer"
},
"coverage": {
"description": "The dataset frontier, ignoring the query's own filters.\n\nend is the latest observed (non-inferred) promotion date, so a promo still\nrunning at the frontier can be told from one that genuinely closed. Either\nbound is null on an empty index.",
"properties": {
"start": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
]
},
"end": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
]
}
},
"required": [
"start",
"end"
],
"type": "object"
},
"returned": {
"type": "integer"
},
"promos": {
"items": {
"properties": {
"promo_id": {
"type": "string"
},
"image_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"retailer": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "The retailer slug — this is the value the retailers filter accepts."
},
"retailer_name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Display name, not filterable."
},
"region": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"channel_type": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"promo_description": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"promo_type": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"promo_depth": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null
},
"promo_currency": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"promo_codes": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"promo_categories": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null
},
"promo_conditions": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null
},
"all_observed_codes": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"description": "Union across every banner folded into this record; the singular field of the same name is unaffected by it."
},
"all_observed_categories": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"description": "Union across every banner folded into this record; the singular field of the same name is unaffected by it."
},
"all_observed_conditions": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"description": "Union across every banner folded into this record; the singular field of the same name is unaffected by it."
},
"promo_gender": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"promo_start_date": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"active_window": {
"anyOf": [
{
"description": "A promo's outer first-to-last span, computed per query.\n\nduration_days is the inclusive calendar span start..end, not a count of\nactive days — the window may contain gaps.",
"properties": {
"start": {
"type": "string"
},
"end": {
"type": "string"
},
"duration_days": {
"type": "integer"
}
},
"required": [
"start",
"end",
"duration_days"
],
"type": "object"
},
{
"type": "null"
}
],
"description": "Null when either span bound is missing."
},
"any_inferred": {
"description": "Whether ANY backing row is forward-projected — campaign-level provenance.",
"type": "boolean"
},
"score": {
"description": "Raw BM25, for ordering only — not a probability, not comparable across tools.",
"type": "number"
}
},
"required": [
"promo_id",
"active_window",
"any_inferred",
"score"
],
"type": "object"
},
"type": "array"
},
"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
},
"query": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"fields": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null
},
"limit": {
"anyOf": [
{
"type": "integer"
},
{
"type": "null"
}
],
"default": null
}
},
"type": "object"
}
},
"required": [
"total_matched",
"coverage",
"returned",
"promos",
"filter_echo"
],
"type": "object"
},
"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"
]
}
},
"oneOf": [
{
"required": [
"result"
]
},
{
"required": [
"error"
]
}
],
"x-fastmcp-wrap-result": true
}