# MCP: Pinterest Trends & Content Intel (`seibs.co/mcp-pinterest-trends-intel`) Actor

MCP server for pinterest-trends-intel. AI-agent tools: search\_trends, get\_top\_pins, get\_pin, and analyze\_profile - Pinterest trend trajectories, top pins, and creator signals from logged-out public surfaces (no API approval). x402 (USDC on Base) and Skyfire ready. For marketers and e-commerce.

- **URL**: https://apify.com/seibs.co/mcp-pinterest-trends-intel.md
- **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community)
- **Categories:** MCP servers, Social media, Marketing
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$5.00 / 1,000 mcp tool calls

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

## MCP: Pinterest Trends & Content Intel

Model Context Protocol (MCP) server wrapping **[pinterest-trends-intel](https://apify.com/seibs.co/pinterest-trends-intel)**. Gives AI agents four tools for Pinterest trend + content intelligence from logged-out public surfaces - no Pinterest API app review, no login.

### Tools

| Tool | Args | Returns |
|---|---|---|
| `search_trends` | `keywords[]`, `region`, `include_pins`, `max_pins_per_query` | Trend records: interest trajectory + seasonality (growing/seasonal/evergreen/declining), growth windows, related terms, category. |
| `get_top_pins` | `query`, `limit`, `include_creators` | Top pins ranked by engagement + a topic rollup (top creators, category mix, dominant-color palette, top link domains). |
| `get_pin` | `pin_url` | Deep pin record (saves, reactions, comments, engagement score, dominant color, board, creator, outbound domain). |
| `analyze_profile` | `username` | Creator audience signal (follower/following/pin/board counts, monthly views, top boards). |

### Run modes

- **`list_tools`** (default, free): emit the tool catalog with JSON schemas + the agentic-payment descriptor.
- **`call_tool`**: invoke one tool. Provide `tool` + `args`.
- **`batch`**: invoke up to 10 `{tool, args}` calls in one run.

```json
{ "mode": "call_tool", "tool": "search_trends", "args": { "keywords": ["home office decor"], "region": "US" } }
```

### Connect it to an MCP client

This Actor is exposed as a remote MCP tool through Apify's hosted MCP server. Point any MCP-compatible client (Claude Desktop, Cursor, VS Code, or an OpenAI / LangChain / LlamaIndex agent) at Apify's server with this Actor enabled:

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=seibs.co/mcp-pinterest-trends-intel",
      "headers": { "Authorization": "Bearer <YOUR_APIFY_TOKEN>" }
    }
  }
}
```

Get a token (free) from **Apify Console -> Settings -> API & Integrations**. The Actor then appears as a callable tool. Run `mode=list_tools` first (free) to fetch every tool's live JSON schema, then call one:

```json
{ "mode": "call_tool", "tool": "search_trends", "args": { } }
```

**Prefer a direct call?** Hit the Actor straight through the Apify API / SDK - no MCP client required:

```python
from apify_client import ApifyClient
client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("seibs.co/mcp-pinterest-trends-intel").call(run_input={
    "mode": "call_tool", "tool": "search_trends", "args": {},
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
```

### Pricing

Flat **$0.005 per MCP tool call**. The upstream pinterest-trends-intel actor charges its own PPE events (`pin_record` $0.004, `trend_enrichment` $0.008, `board_audience_signal` $0.010) directly to the same run as pass-through. `list_tools` is free.

### Agentic payments (x402 / Skyfire)

This server is **x402 (USDC on Base)** and **Skyfire** ready - an AI agent can pay per call with no pre-provisioned API token when the operator enables Apify's MCP monetization. Enable via env: `X402_ENABLED` + `X402_PAY_TO_ADDRESS`, and/or `SKYFIRE_ENABLED` + `SKYFIRE_SELLER_ID`. The `list_tools` catalog advertises whichever rails are enabled.

### Legal & responsible use

Logged-out public Pinterest surfaces only - no login, no accounts, no paywalls. Creator usernames + aggregate follower counts are public profile facts; no private contact data is collected. See the upstream actor's README for the full responsible-use note.

# Actor input Schema

## `mode` (type: `string`):

list\_tools = emit the MCP tool catalog (free). call\_tool = invoke one tool (requires 'tool' + 'args'). batch = invoke a list of {tool, args} calls.

## `tool` (type: `string`):

Required when mode=call\_tool. One of: search\_trends, get\_top\_pins, get\_pin, analyze\_profile.

## `args` (type: `object`):

Arguments for the selected tool. Example for search\_trends: {"keywords": \["home office decor"], "region": "US"}.

## `calls` (type: `array`):

Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: \[{"tool": "search\_trends", "args": {"keywords": \["air fryer recipes"]}}, {"tool": "get\_top\_pins", "args": {"query": "fall outfits"}}]. Max 10 calls per run.

## Actor input object example

```json
{
  "mode": "list_tools",
  "tool": "search_trends",
  "args": {
    "keywords": [
      "home office decor",
      "fall outfits"
    ],
    "region": "US"
  },
  "calls": []
}
```

# 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 = {
    "mode": "list_tools",
    "args": {
        "keywords": [
            "home office decor",
            "fall outfits"
        ],
        "region": "US"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("seibs.co/mcp-pinterest-trends-intel").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 = {
    "mode": "list_tools",
    "args": {
        "keywords": [
            "home office decor",
            "fall outfits",
        ],
        "region": "US",
    },
}

# Run the Actor and wait for it to finish
run = client.actor("seibs.co/mcp-pinterest-trends-intel").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 '{
  "mode": "list_tools",
  "args": {
    "keywords": [
      "home office decor",
      "fall outfits"
    ],
    "region": "US"
  }
}' |
apify call seibs.co/mcp-pinterest-trends-intel --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=seibs.co/mcp-pinterest-trends-intel",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/YIvbsIcIdq3YrCeBy/builds/O00JM6JlRWVxD6iWw/openapi.json