AI Product Recommendation Agent
Pricing
Pay per event
AI Product Recommendation Agent
The AI Product Recommendation Agent helps users find the best products based on their needs using a simple query. It analyzes product listings, reviews, and ratings to provide well-informed recommendations.
5.0 (3)
Pricing
Pay per event
3
Monthly users
18
Runs succeeded
94%
Last modified
a month ago
You can access the AI Product Recommendation Agent programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=matymar/ai-product-recommendation-agent"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1faUsing AI Product Recommendation Agent via Model Context Protocol (MCP) server
MCP server lets you use AI Product Recommendation Agent within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the AI Product Recommendation Agent Actor with the provided input.
1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2 "jsonrpc": "2.0",
3 "id": 1,
4 "method": "tools/call",
5 "params": {
6 "arguments": {
7 "query": "Recommend me a book about music theory. I'\''m a complete beginner and I want to learn the basics.",
8 "modelName": "gpt-4o-mini"
9},
10 "name": "matymar/ai-product-recommendation-agent"
11 }
12}'The response should be: Accepted. You should received response via SSE (JSON) as:
1event: message
2data: {
3 "result": {
4 "content": [
5 {
6 "type": "text",
7 "text": "ACTOR_RESPONSE"
8 }
9 ]
10 }
11}Configure local MCP Server via standard input/output for AI Product Recommendation Agent
You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:
1{
2 "mcpServers": {
3 "actors-mcp-server": {
4 "command": "npx",
5 "args": [
6 "-y",
7 "@apify/actors-mcp-server",
8 "--actors",
9 "matymar/ai-product-recommendation-agent"
10 ],
11 "env": {
12 "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13 }
14 }
15 }
16}You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.
To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.
Pricing
Pricing model
Pay per eventThis Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Actor start per 1 GB
$0.005
Flat fee for starting an Actor run for each 1 GB of memory.
Price per 100 OpenAI tokens for gpt-4o
$0.001
Flat fee for each 100 gpt-4o tokens used.
Price per 100 OpenAI tokens for gpt-4o-mini
$0.00006
Flat fee for each 100 gpt-4o-mini tokens used.
Price per 100 OpenAI tokens for o1
$0.006
Flat fee for each 100 o1tokens used.
Price per 100 OpenAI tokens for o3-mini
$0.00044
Flat fee for each 100 o3-mini tokens used.
