# Apify Portfolio Expansion Planner (`zinin/apify-portfolio-expansion-planner`) Actor

Rank user-supplied candidate niches by public Store opportunity and textual adjacency to a user-supplied portfolio. Public Store API only for candidates, no portfolio fetching.

- **URL**: https://apify.com/zinin/apify-portfolio-expansion-planner.md
- **Developed by:** [Tim Zinin](https://apify.com/zinin) (community)
- **Categories:** MCP servers, Developer tools
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Apify Portfolio Expansion Planner

Rank user-supplied candidate niches by public Store opportunity and textual adjacency
to a user-supplied portfolio. Portfolio data is BYOD and never fetched from Apify.
The report separates supplied portfolio context from public Store evidence and exposes bounded deterministic scores.

### Pricing

Pay-per-event:

- `apify-actor-start`: $0.005
- `result-found`: $0.15

### What you get

- Candidate niches ranked by public Store opportunity and BYOD portfolio adjacency.
- Deterministic adjacency, novelty, priority, rationale, and coverage fields.
- Explicit separation between supplied portfolio text and Store-verified evidence.
- One compact dataset report plus a replay-safe `OUTPUT` summary.

### How to use

1. Click **Try for free** and provide at least one bounded portfolio actor object.
2. Add candidate queries and set a unique `requestId`.
3. Start the run and read ranked expansions from the dataset row.

### Input

```json
{
  "schemaVersion": "1.0",
  "requestId": "plan-001",
  "portfolioActors": [
    {
      "id": "a1",
      "name": "Apify Store Idea Validator",
      "title": "Apify Store Idea Validator",
      "description": "Scores ideas against public Store evidence.",
      "categories": ["MCP_SERVERS", "DEVELOPER_TOOLS"]
    }
  ],
  "candidateQueries": ["store opportunity", "pricing benchmark"],
  "maxResults": 10,
  "freshnessMinutes": 60,
  "detailLevel": "compact"
}
```

Portfolio data is validated as supplied evidence and is never fetched or treated as
Store-verified. The business envelope is written to KVS key `OUTPUT`; replaying the
same `requestId` cannot create another Dataset row or `result-found` charge.

#### Related tools

Related tools for adjacent workflows in in-house factory tooling.

| Actor | What it does |
|---|---|
| [Apify Market Gap Finder](https://apify.com/zinin/apify-market-gap-finder) | Pair it in the in-house factory tooling workflow: Compare user-declared niches against the public Apify Store and rank evidence-backed market gaps |
| [Apify Niche Demand Radar](https://apify.com/zinin/apify-niche-demand-radar) | Pair it in the in-house factory tooling workflow: Produce a current demand-direction snapshot for one declared niche using observed public Apify Store user... |
| [Apify Pricing Benchmark Advisor](https://apify.com/zinin/apify-pricing-benchmark-advisor) | Pair it in the in-house factory tooling workflow: Summarize visible public Apify Store event-price distributions for a declared cohort |
| [Apify Actor Idea Validator](https://apify.com/zinin/apify-actor-idea-validator) | Pair it in the in-house factory tooling workflow: Assess one proposed Apify Actor idea against public Store similarity, activity, quality, competition and... |

### FAQ / Support

**Is portfolio text fetched from an account?** No. Portfolio objects are supplied by the caller and are never fetched from Apify.

**What this is NOT.** It is not a portfolio editor, financial forecast, or guarantee that a candidate will succeed. Report bugs through the Actor page.

### Output

```json
{
  "schemaVersion": "1.0",
  "requestId": "plan-001",
  "reportType": "portfolio_expansion_plan",
  "generatedAt": "2026-07-31T00:00:00.000Z",
  "sampleConfidence": "low",
  "portfolioActorCount": 1,
  "expansions": [
    {
      "rank": 1,
      "candidate": "store opportunity",
      "priority": 54.2,
      "adjacency": 40,
      "novelty": 60
    }
  ]
}
```

# Actor input Schema

## `schemaVersion` (type: `string`):

Contract version.

## `requestId` (type: `string`):

Idempotency key.

## `maxResults` (type: `integer`):

Maximum nested expansions.

## `freshnessMinutes` (type: `integer`):

Maximum cache age.

## `detailLevel` (type: `string`):

Output detail mode.

## `portfolioActors` (type: `array`):

Existing portfolio used for adjacency scoring.

## `candidateQueries` (type: `array`):

Candidate niches to evaluate for portfolio expansion.

## Actor input object example

```json
{
  "schemaVersion": "1.0",
  "requestId": "plan-daily-prefill-001",
  "maxResults": 10,
  "freshnessMinutes": 60,
  "detailLevel": "compact",
  "portfolioActors": [
    {
      "id": "a1",
      "name": "Store tools",
      "title": "Store research tools",
      "description": "Tools for discovering and comparing Store opportunities.",
      "categories": [
        "MCP_SERVERS"
      ]
    }
  ],
  "candidateQueries": [
    "store opportunity",
    "pricing benchmark"
  ]
}
```

# Actor output Schema

## `OUTPUT` (type: `string`):

Compact business OUTPUT envelope stored in the default key-value store.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "schemaVersion": "1.0",
    "requestId": "plan-daily-prefill-001",
    "maxResults": 10,
    "freshnessMinutes": 60,
    "detailLevel": "compact",
    "portfolioActors": [
        {
            "id": "a1",
            "name": "Store tools",
            "title": "Store research tools",
            "description": "Tools for discovering and comparing Store opportunities.",
            "categories": [
                "MCP_SERVERS"
            ]
        }
    ],
    "candidateQueries": [
        "store opportunity",
        "pricing benchmark"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("zinin/apify-portfolio-expansion-planner").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "schemaVersion": "1.0",
    "requestId": "plan-daily-prefill-001",
    "maxResults": 10,
    "freshnessMinutes": 60,
    "detailLevel": "compact",
    "portfolioActors": [{
            "id": "a1",
            "name": "Store tools",
            "title": "Store research tools",
            "description": "Tools for discovering and comparing Store opportunities.",
            "categories": ["MCP_SERVERS"],
        }],
    "candidateQueries": [
        "store opportunity",
        "pricing benchmark",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("zinin/apify-portfolio-expansion-planner").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "schemaVersion": "1.0",
  "requestId": "plan-daily-prefill-001",
  "maxResults": 10,
  "freshnessMinutes": 60,
  "detailLevel": "compact",
  "portfolioActors": [
    {
      "id": "a1",
      "name": "Store tools",
      "title": "Store research tools",
      "description": "Tools for discovering and comparing Store opportunities.",
      "categories": [
        "MCP_SERVERS"
      ]
    }
  ],
  "candidateQueries": [
    "store opportunity",
    "pricing benchmark"
  ]
}' |
apify call zinin/apify-portfolio-expansion-planner --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=zinin/apify-portfolio-expansion-planner",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/YX7XLWkh9FbFnJ2HB/builds/a7k7Udl0hN6UlS5ry/openapi.json