`get_model_landscape`

Pack: ai-briefing · Endpoint: https://gateway.pipeworx.io/ai-briefing/mcp

Get recent AI model releases — which providers shipped what, when, and their key capabilities. Returns model names, companies, dates, and feature summaries.

Parameters

Name	Type	Required	Description
`days`	number	no	Look back N days (default 30)

Example call

Arguments

{
  "days": 30
}

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":"get_model_landscape","arguments":{"days":30}}}'

TypeScript (@pipeworx/sdk)

import { Pipeworx } from '@pipeworx/sdk';
const pipeworx = new Pipeworx();

const result = await pipeworx.call('get_model_landscape', {
  "days": 30
});

More examples

{
  "days": 14
}

Response shape

Always returns: period, model_releases, models

Field	Type	Description
`period`	string	Time period description
`model_releases`	number	Number of model releases found
`models`	array	Model release developments

Full JSON Schema

{
  "type": "object",
  "properties": {
    "period": {
      "type": "string",
      "description": "Time period description"
    },
    "model_releases": {
      "type": "number",
      "description": "Number of model releases found"
    },
    "models": {
      "type": "array",
      "description": "Model release developments",
      "items": {
        "type": "object",
        "properties": {
          "title": {
            "type": "string",
            "description": "Model name or release title"
          },
          "summary": {
            "type": "string",
            "description": "Model description and capabilities"
          },
          "url": {
            "type": "string",
            "description": "Source URL"
          },
          "source": {
            "type": "string",
            "description": "Source identifier"
          },
          "importance": {
            "type": "string",
            "description": "Importance level"
          },
          "published_at": {
            "type": "string",
            "description": "Publication timestamp"
          },
          "tags": {
            "type": "array",
            "description": "Associated tags"
          }
        }
      }
    }
  },
  "required": [
    "period",
    "model_releases",
    "models"
  ]
}

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.

get_model_landscape