what_happened
Pack: ai-briefing · Connect: https://pipeworx.io/mcp (see Connect below for a single-pack URL)
No MCP client? Call it directly: GET https://gateway.pipeworx.io/v1/tools/what_happened for the schema, then POST the same URL with its arguments for the data.
Ask natural language questions about recent tools and developments (e.g., ‘any new MCP servers this week’, ‘latest Claude tools’). Returns the most relevant developments.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
question | string | yes | Your question about recent AI developments |
days | number | no | Look back N days (default 30) |
Example call
Arguments
{
"question": "any new MCP servers this week"
}
curl
curl -X POST https://gateway.pipeworx.io/ai-briefing/mcp \
-H 'Content-Type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"what_happened","arguments":{"question":"any new MCP servers this week"}}}'
TypeScript (@pipeworx/sdk)
import { Pipeworx } from '@pipeworx/sdk';
const pipeworx = new Pipeworx();
const result = await pipeworx.call('what_happened', {
"question": "any new MCP servers this week"
});
More examples
{
"question": "latest Claude tools",
"days": 14
}
Response shape
Always returns: question, keywords_used, period, total, developments
| Field | Type | Description |
|---|---|---|
question | string | Original natural language question |
keywords_used | array | Extracted keywords from question |
period | string | Time period description |
total | number | Number of matching developments found |
developments | array | Most relevant developments |
Full JSON Schema
{
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "Original natural language question"
},
"keywords_used": {
"type": "array",
"description": "Extracted keywords from question",
"items": {
"type": "string"
}
},
"period": {
"type": "string",
"description": "Time period description"
},
"total": {
"type": "number",
"description": "Number of matching developments found"
},
"developments": {
"type": "array",
"description": "Most relevant developments",
"items": {
"type": "object",
"properties": {
"title": {
"type": "string",
"description": "Development title"
},
"summary": {
"type": "string",
"description": "Development summary"
},
"url": {
"type": "string",
"description": "Source URL"
},
"source": {
"type": "string",
"description": "Source identifier"
},
"category": {
"type": "string",
"description": "Development category"
},
"importance": {
"type": "string",
"description": "Importance level"
},
"published_at": {
"type": "string",
"description": "Publication timestamp"
}
}
}
}
},
"required": [
"question",
"keywords_used",
"period",
"total",
"developments"
]
}
Connect
Add this to your MCP client config — every tool in the catalog, including this one — or use one-click install buttons:
{
"mcpServers": {
"pipeworx": {
"url": "https://pipeworx.io/mcp"
}
}
}
Connect to just the ai-briefing pack
{
"mcpServers": {
"ai-briefing": {
"url": "https://gateway.pipeworx.io/ai-briefing/mcp"
}
}
}
See Getting Started for client-specific install steps.