# AI Brand Monitor (MCP) (`scrap_them_all/ai-brand-monitor-mcp`) Actor

MCP-friendly Actor that tracks how LLM-search engines (Perplexity, You.com, Phind, Brave AI) describe a brand. Scrapes the public answer pages, extracts citations, computes share-of-voice. Zero LLM API cost.

- **URL**: https://apify.com/scrap\_them\_all/ai-brand-monitor-mcp.md
- **Developed by:** [scrap\_them\_all](https://apify.com/scrap_them_all) (community)
- **Categories:** AI, Automation, MCP servers
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 ai brand monitor cards

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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use 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

## AI Brand Monitor (MCP)

### What does AI Brand Monitor do?

Pass a brand name and get back a structured report on how **LLM-search platforms** describe it. The actor queries Perplexity, You.com, Phind, and Brave AI in parallel, parses each platform's answer + citations, then computes brand-mention rate, competitor share-of-voice, sentiment per platform, and most-cited source domains. Returns a deterministic LLM-ready markdown report. **Zero LLM API cost server-side** - we hit the public answer pages directly.

> Designed for AI-SEO / brand monitoring teams: track if your brand surfaces when users ask LLM-search engines about your category, who competes against you in the AI answer panel, and which third-party sources LLMs cite.

### Why use it from an AI agent?

- **Multi-platform in one call** - 4 LLM-search engines queried in parallel.
- **Deterministic** - no LLM call inside, same input today = same metrics tomorrow.
- **Citation-aware** - returns the exact URLs each platform cites, so you can investigate why your brand isn't surfaced.
- **Share of voice** - explicit metric for brand vs competitor when you supply both.
- **Sentiment per platform** - lexicon-based, no LLM, picks up positive/negative skew across the answer text.

### Modes

#### A. Brand Pulse (default)

Default question template: *"What do people say about [brand] for [category]?"*. Use this for routine brand health monitoring.

```json
{
    "mode": "brand_pulse",
    "brand": "Linear",
    "category": "project management"
}
````

#### B. Competitor Compare

Asks each platform: *"\[brand] vs \[competitor] for \[category]"*. Returns explicit share-of-voice between the two.

```json
{
    "mode": "competitor_compare",
    "brand": "Linear",
    "competitor": "Asana",
    "category": "project management"
}
```

#### C. Custom Query

Ship your exact question. The actor queries each platform with the verbatim string and parses the response.

```json
{
    "mode": "custom_query",
    "brand": "Linear",
    "customQuery": "What's the best project management tool for engineering teams in 2026?"
}
```

### Output

```json
{
    "meta": {
        "brand": "Linear",
        "competitor": "Asana",
        "mode": "competitor_compare",
        "query": "Linear vs Asana for project management",
        "scrapedAt": "2026-05-08T15:00:00Z"
    },
    "intelligence": {
        "platformsQueried": 4,
        "platformsAnswered": 3,
        "brandMentionCount": 3,
        "competitorMentionCount": 2,
        "shareOfVoice": 0.6,
        "totalCitations": 28,
        "uniqueDomains": 19,
        "topCitedDomains": [
            { "domain": "linear.app", "count": 5 },
            { "domain": "asana.com", "count": 4 }
        ],
        "sentimentDistribution": { "positive": 2, "neutral": 1, "negative": 0, "unknown": 1 },
        "perPlatform": [
            { "platform": "perplexity", "answered": true, "brandMentioned": true, "competitorMentioned": true, "sentiment": "positive", "citationsCount": 8 }
        ]
    },
    "responses": [
        {
            "platform": "perplexity",
            "query": "Linear vs Asana for project management",
            "answer": "Linear is generally praised for its speed and modern UI...",
            "citations": [{ "url": "https://linear.app/...", "domain": "linear.app" }],
            "answerLength": 423,
            "fetchedAt": "2026-05-08T15:00:00Z"
        }
    ],
    "llm_ready": {
        "summary": "Linear: queried 4 LLM-search platforms (3 answered)...",
        "markdown_report": "### AI Brand Monitor Report\n..."
    }
}
```

### Pricing (PPE)

| Mode | Price per call |
| --- | --- |
| All modes | $0.001 actor start + $0.005 brand monitor card = **$0.006/call** |

The Actor uses Apify residential proxy because all 4 platforms sit behind Cloudflare Bot Management. Proxy bandwidth (~100-300 KB per platform call x 4 platforms) adds operator cost ~$0.001-0.002 per call. Net margin remains positive.

### Platforms covered

| Platform | What we extract | Reliability |
| --- | --- | --- |
| Perplexity (`perplexity.ai/search`) | answer text + citation URLs | High - clean public page |
| You.com (`you.com/search`) | AI answer (from `__NEXT_DATA__`) + result links | Medium - schema changes |
| Phind (`phind.com/search`) | answer + citation URLs | Medium - dev-focused, narrower coverage |
| Brave AI (`search.brave.com/search?summary=1`) | AI summary + organic result URLs | Medium - summary not always present |

ChatGPT and Claude.ai are **not covered** in v0.1 because their public chat interfaces require auth and have aggressive bot detection. Future v0.2 may add ChatGPT Atlas (`shared chat URLs`) and Google AI Overviews (via SERP scraping).

### Limits & caveats

- **Anti-bot variance**: any of the 4 platforms can return blocked-page HTML on a given run. The actor never aborts on a single platform's failure - the analyzer treats missing answers as 'no answer' and the report flags which platforms succeeded.
- **Sentiment is lexicon-based**, not LLM. It picks up direction (positive vs negative) but misses sarcasm and domain-specific jargon.
- **Mention detection** is exact-word-boundary regex on the brand string. "Linear" matches "Linear" but not "Linear app"-typos.
- **Schema drift**: each platform's HTML structure changes occasionally. The parsers fall back to `og:description` meta as a last-resort answer source.

### Calling from an MCP agent

Via Apify MCP server (`mcp.apify.com`) as `call-actor` with name `ai-brand-monitor-mcp`. Direct Standby HTTP:

```bash
curl -X POST -H 'Content-Type: application/json' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -d '{"mode":"brand_pulse","brand":"Linear","category":"project management"}' \
  https://<actor-standby-url>
```

### Pairs naturally with

- `web-company-intelligence-mcp` to enrich the brand's homepage tech stack
- `reddit-intelligence-mcp` for community sentiment beyond LLM-search platforms
- `github-org-intelligence-mcp` if the brand is a developer tool

### Sources & legality

- All requests hit publicly accessible search/answer pages. No auth tokens, no API keys, no LLM provider billing.
- Browser-like User-Agent, residential IP rotation - mimics a normal user looking up the brand.
- Citation URLs and answer text are returned verbatim from the public page; no derivative work or republication.

# Actor input Schema

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

brand\_pulse for routine monitoring, competitor\_compare for A vs B, or custom\_query to send your own exact question.

## `brand` (type: `string`):

Required. The brand to monitor (e.g. 'Linear', 'Notion', 'Stripe').

## `competitor` (type: `string`):

Required for competitor\_compare. The competing brand (e.g. 'Asana' if brand is 'Linear').

## `category` (type: `string`):

Optional context to make the prompt sharper (e.g. 'project management', 'CRM', 'invoicing'). Used in the default question templates.

## `customQuery` (type: `string`):

Required for custom\_query. The exact question to send to each LLM-search platform (e.g. 'Compare Linear and Asana for engineering teams').

## `platforms` (type: `array`):

Which LLM-search platforms to query. Default = all four. Each query is independent - one platform failing doesn't stop the others.

## Actor input object example

```json
{
  "mode": "brand_pulse",
  "category": "project management",
  "platforms": [
    "perplexity",
    "you",
    "phind",
    "brave"
  ]
}
```

# Actor output Schema

## `card` (type: `string`):

No description

## `dataset` (type: `string`):

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("scrap_them_all/ai-brand-monitor-mcp").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("scrap_them_all/ai-brand-monitor-mcp").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 '{}' |
apify call scrap_them_all/ai-brand-monitor-mcp --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=scrap_them_all/ai-brand-monitor-mcp",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "AI Brand Monitor (MCP)",
        "description": "MCP-friendly Actor that tracks how LLM-search engines (Perplexity, You.com, Phind, Brave AI) describe a brand. Scrapes the public answer pages, extracts citations, computes share-of-voice. Zero LLM API cost.",
        "version": "0.1",
        "x-build-id": "aAKUJSWQR7GFLwWkJ"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scrap_them_all~ai-brand-monitor-mcp/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scrap_them_all-ai-brand-monitor-mcp",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scrap_them_all~ai-brand-monitor-mcp/runs": {
            "post": {
                "operationId": "runs-sync-scrap_them_all-ai-brand-monitor-mcp",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scrap_them_all~ai-brand-monitor-mcp/run-sync": {
            "post": {
                "operationId": "run-sync-scrap_them_all-ai-brand-monitor-mcp",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "required": [
                    "mode",
                    "brand"
                ],
                "properties": {
                    "mode": {
                        "title": "Mode",
                        "enum": [
                            "brand_pulse",
                            "competitor_compare",
                            "custom_query"
                        ],
                        "type": "string",
                        "description": "brand_pulse for routine monitoring, competitor_compare for A vs B, or custom_query to send your own exact question.",
                        "default": "brand_pulse"
                    },
                    "brand": {
                        "title": "Brand name (modes A, B, C)",
                        "type": "string",
                        "description": "Required. The brand to monitor (e.g. 'Linear', 'Notion', 'Stripe')."
                    },
                    "competitor": {
                        "title": "Competitor brand (mode B)",
                        "type": "string",
                        "description": "Required for competitor_compare. The competing brand (e.g. 'Asana' if brand is 'Linear')."
                    },
                    "category": {
                        "title": "Category / use-case (modes A, B)",
                        "type": "string",
                        "description": "Optional context to make the prompt sharper (e.g. 'project management', 'CRM', 'invoicing'). Used in the default question templates."
                    },
                    "customQuery": {
                        "title": "Custom question (mode C)",
                        "type": "string",
                        "description": "Required for custom_query. The exact question to send to each LLM-search platform (e.g. 'Compare Linear and Asana for engineering teams')."
                    },
                    "platforms": {
                        "title": "Platforms to query",
                        "type": "array",
                        "description": "Which LLM-search platforms to query. Default = all four. Each query is independent - one platform failing doesn't stop the others.",
                        "items": {
                            "type": "string"
                        },
                        "default": [
                            "perplexity",
                            "you",
                            "phind",
                            "brave"
                        ]
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```