search_developments
Pack: ai-briefing · Endpoint: https://gateway.pipeworx.io/ai-briefing/mcp
No MCP client? Call it directly: GET https://gateway.pipeworx.io/v1/tools/search_developments for the schema, then POST the same URL with its arguments for the data.
Search for new tools, APIs, MCP servers, and frameworks by keyword (e.g., ‘vector databases’, ‘Claude integrations’). Returns matching developments with descriptions and sources.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
query | string | yes | Search query |
limit | number | no | Max results (default 10) |
Example call
Arguments
{
"query": "vector databases"
}
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":"search_developments","arguments":{"query":"vector databases"}}}'
TypeScript (@pipeworx/sdk)
import { Pipeworx } from '@pipeworx/sdk';
const pipeworx = new Pipeworx();
const result = await pipeworx.call('search_developments', {
"query": "vector databases"
});
More examples
{
"query": "Claude integrations",
"limit": 5
}
Response shape
Always returns: query, total, results
| Field | Type | Description |
|---|---|---|
query | string | Search query executed |
total | number | Number of results found |
results | array | Matching developments |
Full JSON Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query executed"
},
"total": {
"type": "number",
"description": "Number of results found"
},
"results": {
"type": "array",
"description": "Matching 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": [
"query",
"total",
"results"
]
}
Connect
Add this to your MCP client config, or use one-click install buttons:
{
"mcpServers": {
"ai-briefing": {
"url": "https://gateway.pipeworx.io/ai-briefing/mcp"
}
}
}
See Getting Started for client-specific install steps.