Snapchat Explore Search Across Spotlight, Lenses & Places: MCP config, n8n workflow and API

What a run costs

Every run pays a start fee plus a price per result. On the Free plan this Actor's start fee is $0.40 (the start event, $0.10 per GB, times its default 4 GB of memory), $0.12 on Business; results cost $0.99 per 1,000 results (pay per event). Checked 2026-11-12.

Plus Apify platform usage for the run, which the caller pays. A smaller memory setting lowers the start fee if the Actor still finishes. Prices can change; the Store pricing tab is the source of truth.

An example record

One record as the Actor's own README shows it (published by the Actor, not a run of ours; long values shortened). Your runs return records shaped like this.

{
  "query": "food",
  "resultType": "spotlight",
  "rank": 1,
  "scrapedAt": "2026-11-07T06:59:37.000000+00:00",
  "href": "https://www.snapchat.com/@foodasmr3/spotlight/W7_EDlXWTBiXAEEniNoMPwAAYZnV3bm5oeGVlAZ84zAenAZ84y_B7AAAAAQ",
  "storyId": "W7_EDlXWTBiXAEEniNoMPwAAYZnV3bm5oeGVlAZ84zAenAZ84y_B7AAAAAQ",
  "rawSnapId": "W7_EDlXWTBiXAEEniNoMPwAAYZnV3bm5oeGVlAZ84zAenAZ84y_B7AAAAAQ",
  "creatorUsername": "foodasmr3",
  "creatorDisplayName": "FOOD",
  "title": "Mukbang Magic: Spicy Ramen & Dumplings Feast!",
  "description": "Get ready for a mouthwatering mukbang experience...",
  "keywords": [
    "how to eat ramen",
    "spicy ramen recipe",
    "ramen bowl"
  ],
  "viewCount": 68553,
  "likeCount": 5972,
  "commentCount": 83,
  "shareCount": 1530,
  "thumbnailUrl": "https://cf-st.sc-cdn.net/d/...",
  "videoPreviewUrl": "https://cf-st.sc-cdn.net/d/...",
  "mediaUrl": "https://cf-st.sc-cdn.net/d/...",
  "gradientFrom": "#2b2b35",
  "gradientTo": "#16191c"
}

MCP config

One URL works in every client: https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses. It exposes this Actor as a tool, plus fetch-actor-details so the agent can read the input schema before calling it. Pick your client:

claude mcp add --transport http snapchat-explore-search-across-spotlight-lenses "https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses"

{
  "mcpServers": {
    "snapchat-explore-search-across-spotlight-lenses": {
      "command": "npx",
      "args": [
        "-y",
        "@apify/actors-mcp-server",
        "--tools",
        "fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses"
      ],
      "env": {
        "APIFY_TOKEN": "YOUR_APIFY_TOKEN"
      }
    }
  }
}

{
  "mcpServers": {
    "snapchat-explore-search-across-spotlight-lenses": {
      "url": "https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses",
      "headers": {
        "Authorization": "Bearer ${env:APIFY_TOKEN}"
      }
    }
  }
}

{
  "inputs": [
    {
      "type": "promptString",
      "id": "apify-token",
      "description": "Apify API token",
      "password": true
    }
  ],
  "servers": {
    "snapchat-explore-search-across-spotlight-lenses": {
      "type": "http",
      "url": "https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses",
      "headers": {
        "Authorization": "Bearer ${input:apify-token}"
      }
    }
  }
}

https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses

[mcp_servers.snapchat-explore-search-across-spotlight-lenses]
url = "https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses"
bearer_token_env_var = "APIFY_TOKEN"

gemini mcp add -t http -s user -H "Authorization: Bearer $APIFY_TOKEN" snapchat-explore-search-across-spotlight-lenses "https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses"

https://mcp.apify.com/?tools=fetch-actor-details,vexaloom-labs/snapchat-explore-search-across-spotlight-lenses

n8n workflow

A manual and a daily trigger call the Actor through the HTTP Request node with your Apify token, then hand each record to the destination you pick. The Actor input sits in the request body, already filled with the example below.

• Run by hand
• Every day
• Run Apify Actor

{
  "name": "Snapchat Explore Search Across Spotlight, Lenses & Places to n8n only",
  "nodes": [
    {
      "id": "7eca3f6e-2777-4bcd-a018-6c187d10540b",
      "name": "Run by hand",
      "type": "n8n-nodes-base.manualTrigger",
      "typeVersion": 1,
      "position": [
        0,
        0
      ],
      "parameters": {}
    },
    {
      "id": "738eea7e-fbb9-4417-a465-74eeb6299163",
      "name": "Every day",
      "type": "n8n-nodes-base.scheduleTrigger",
      "typeVersion": 1.2,
      "position": [
        0,
        200
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "triggerAtHour": 8
            }
          ]
        }
      },
      "notes": "Activate the workflow to run on this schedule."
    },
    {
      "id": "bd5346c2-f156-4108-abb0-58e154663643",
      "name": "Run Apify Actor",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [
        260,
        100
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/actors/vexaloom-labs~snapchat-explore-search-across-spotlight-lenses/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\n  \"queries\": [\n    \"food\"\n  ],\n  \"mode\": \"all\",\n  \"maxResultsPerQuery\": 3,\n  \"page\": 1\n}",
        "options": {
          "timeout": 310000
        }
      },
      "notes": "Actor: vexaloom-labs/snapchat-explore-search-across-spotlight-lenses. Select a Header Auth credential: name Authorization, value Bearer + your Apify token. Edit the JSON body to change the input.",
      "notesInFlow": false
    },
    {
      "id": "dd72883e-79e4-4ec3-a4a9-b36ee5ec2133",
      "name": "Setup",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        0,
        -370
      ],
      "parameters": {
        "content": "## Snapchat Explore Search Across Spotlight, Lenses & Places\n\nSource: [vexaloom-labs/snapchat-explore-search-across-spotlight-lenses](https://apify.com/vexaloom-labs/snapchat-explore-search-across-spotlight-lenses) on Apify.\n\n1. In **Run Apify Actor**, create a Header Auth credential: name `Authorization`, value `Bearer YOUR_APIFY_TOKEN` with your token.\n2. Click **Execute workflow**. Each record arrives as one n8n item.\n3. Edit the JSON body of **Run Apify Actor** to change the input.\n\nGenerated by recipeforagents.com. Validated, not executed: runs are billed to your Apify account.",
        "height": 340,
        "width": 460,
        "color": 6
      }
    }
  ],
  "connections": {
    "Run by hand": {
      "main": [
        [
          {
            "node": "Run Apify Actor",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Every day": {
      "main": [
        [
          {
            "node": "Run Apify Actor",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "pinData": {},
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "meta": {
    "templateCredsSetupCompleted": false
  },
  "tags": []
}

All 7 destination variants pass the same checks at build time. Built-in nodes only, at versions n8n has shipped since 1.80: they import on n8n Cloud and older self-hosted instances without community nodes. Prefer Apify's own node? The verified community node @apify/n8n-nodes-apify runs the same Actor with OAuth sign-in on n8n Cloud.

Call it from code

Run the Actor from a script or your own agent framework with the Apify API. The call waits for the run to finish and returns the records. The input is the example below.

curl -X POST "https://api.apify.com/v2/actors/vexaloom-labs~snapchat-explore-search-across-spotlight-lenses/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries":["food"],"mode":"all","maxResultsPerQuery":3,"page":1}'

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
    "queries": [
        "food",
    ],
    "mode": "all",
    "maxResultsPerQuery": 3,
    "page": 1,
}

run = client.actor("vexaloom-labs/snapchat-explore-search-across-spotlight-lenses").call(run_input=run_input)
if run is None:
    raise RuntimeError("The Actor run could not be started")
print(run.status, "dataset", run.default_dataset_id)
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const input = {
  "queries": [
    "food"
  ],
  "mode": "all",
  "maxResultsPerQuery": 3,
  "page": 1
};

const run = await client.actor("vexaloom-labs/snapchat-explore-search-across-spotlight-lenses").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, items[0]);

Example input

These values come from the Actor's Store prefill and required defaults. Change the search, URL or limit before your first run.

{
  "queries": [
    "food"
  ],
  "mode": "all",
  "maxResultsPerQuery": 3,
  "page": 1
}

1 more optional field on the Store input tab.

What your agent receives

Each run returns a list of records. The Actor publishes 111 fields, starting with resultType, href, storyId, rawSnapId.

71 more fields in the full output.

Agent skill

A SKILL.md in the open Agent Skills format. It teaches Claude Code, Codex and other skill-aware agents when to call this Actor, how to build the input and how to read the result, using the API directly.

---
name: snapchat-explore-search-across-spotlight-lenses
description: "A dataset row per Snapchat Explore search result: Spotlight video, AR lens, related topic, user, public profile, show episode, publisher or place, with engagement counts and canonical links. Runs the Apify Actor vexaloom-labs/snapchat-explore-search-across-spotlight-lenses. Use when the user needs Snapchat data with fields such as query, resultType, rank, scrapedAt, href, storyId and an Apify token is available."
compatibility: "Needs network access, curl, and an APIFY_TOKEN environment variable. Runs are billed to the token owner's Apify account."
metadata:
  actor: "vexaloom-labs/snapchat-explore-search-across-spotlight-lenses"
  store-url: "https://apify.com/vexaloom-labs/snapchat-explore-search-across-spotlight-lenses"
---

# Snapchat Explore Search Across Spotlight, Lenses & Places

Use this skill to fetch Snapchat data with the Apify Actor `vexaloom-labs/snapchat-explore-search-across-spotlight-lenses` and work with the returned rows.

## Before running

1. Check that `APIFY_TOKEN` is set in the environment. Never print it or write it to a file.
2. Build `input.json` from the user's request using the fields below. Keep limits small for a first run.
3. Confirm the search terms or URLs with the user if the request is ambiguous.

## Input fields

| Field | Type | Meaning |
| --- | --- | --- |
| `queries` | array | One or more public Snapchat Explore keywords, e.g. food, travel, selenagomez. Legacy keywords, query, searchQueries and searchTerms inputs are still accepted in code. |
| `mode` | string | Result family to return. 'Users' includes both Snapchat user cards and public profiles; 'Profiles' returns public profiles only. |
| `maxResultsPerQuery` | integer | Records returned for each query in the selected page window. Legacy maxResults and maxItems inputs are still accepted in code. |
| `page` | integer | Snapchat exposes one fixed result set per query with no cursor. Page 1 returns the first maxResultsPerQuery records, page 2 the next batch, and so on. Legacy startPage is still accepted in code. |

Example `input.json` (the Actor's published prefill):

```json
{
  "queries": [
    "food"
  ],
  "mode": "all",
  "maxResultsPerQuery": 3,
  "page": 1
}
```

## Run

```bash
curl -sS -X POST "https://api.apify.com/v2/acts/vexaloom-labs~snapchat-explore-search-across-spotlight-lenses/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d @input.json > results.json
```

The call waits for the run to finish and returns the dataset items as a JSON array. If the run needs more than 300 seconds the API answers with HTTP 408; then start the run with `POST /v2/acts/vexaloom-labs~snapchat-explore-search-across-spotlight-lenses/runs`, poll `GET /v2/actor-runs/{runId}` until `SUCCEEDED`, and read `GET /v2/datasets/{defaultDatasetId}/items`.

## Output

Each item is one record. Published fields include: `query`, `resultType`, `rank`, `scrapedAt`, `href`, `storyId`, `rawSnapId`, `thumbnailUrl`, `mediaUrl`, `videoPreviewUrl`, `creatorUsername`, `creatorDisplayName`, `teaserText`, `rawCaption`, `title`, `snapTitle`, `description`, `snapDescription`, `caption`, `keywords`.

Summarise what was found, cite the record URLs when present, and say how many items came back. Do not invent values for empty fields.

• Claude Code: save it as ~/.claude/skills/snapchat-explore-search-across-spotlight-lenses/SKILL.md, or .claude/skills/snapchat-explore-search-across-spotlight-lenses/SKILL.md in a project.
• Codex and other agents: ~/.agents/skills/snapchat-explore-search-across-spotlight-lenses/SKILL.md, or .agents/skills/snapchat-explore-search-across-spotlight-lenses/ in a project.
• Or let the skills CLI place it for your agent: npx skills add https://recipeforagents.com --skill snapchat-explore-search-across-spotlight-lenses
• Set APIFY_TOKEN in the agent's environment.

Troubleshooting

Every fix in one place