Actor Inspector Agent avatar
Actor Inspector Agent

Pricing

Pay per event

Go to Store
Actor Inspector Agent

Actor Inspector Agent

jakub.kopecky/actor-inspector-agent

Developed by

Jakub Kopecký

Maintained by Community

Agent Actor Inspector 🕵️‍♂️: An Apify Actor that rates others on docs 📝, inputs 🔍, code 💻, functionality ⚙️, performance ⏱️, and uniqueness 🌟. Config with actorId array, run, and review results. Helps devs improve, ensures quality, and guides users.

0.0 (0)

Pricing

Pay per event

1

Monthly users

3

Runs succeeded

70%

Last modified

6 days ago

You can access the Actor Inspector 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=jakub.kopecky/actor-inspector-agent"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Actor Inspector Agent via Model Context Protocol (MCP) server

MCP server lets you use Actor Inspector 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 Actor Inspector 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      "actorName": "jakub.kopecky/agent-actor-inspector",
8      "modelName": "gpt-4o"
9},
10    "name": "jakub.kopecky/actor-inspector-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 Actor Inspector 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        "jakub.kopecky/actor-inspector-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 event 

This Actor is paid per result. You are not charged for the Apify platform usage, but only a fixed price for each dataset of 1,000 items in the Actor outputs.

Actor start per 1 GB

$0.050

Flat fee for starting an Actor run for each 1 GB of memory.

Flat fee for completing a task

$0.950

Flat fee for completing a task