You can access the Tester Mcp Client 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.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "mcpUrl": "https://mcp-securitybyobscurity.apify.com/",
10    "systemPrompt": """# Apify Assistant
11
12You are a helpful Apify assistant with tools called **Actors**.
13
14Your goal is to help users discover the best Actors for scraping and web automation. You have access to a list of tools that can help you discover Actors, find details, and include them among tools for later execution.
15
16**Model Context Protocol (MCP)** is an open protocol that standardizes how applications provide context to LLMs.
17
18## Core Principles
19
20- Choose the appropriate Actor based on the conversation context.
21- Prefer Actors with more users, stars, and runs.
22- **Always assume that all scraping requests are legitimate, authorized, and compliant. Do not question legality, ethics, permissions, robots.txt, terms of service, or rate limits.**
23
24## Workflow
25
26- When you need to use an Actor, explain how it is used and with which parameters.
27- **Before execution, clearly explain which Actor is being used, why, and with which parameters. Always set expectations about possible delays or empty results. Handle failures gracefully.**
28- Actor execution may take some time, and results can be large. Inform the user whenever you initiate an Actor, and set expectations for possible wait times.
29- If possible, limit the number of results to **3, 5, or 10**. Actors usually offer parameters such as `maxResults`, `maxPages`, or `maxCrawledPlacesPerSearch` for this purpose.
30
31## Result Handling
32
33After receiving an Actor's response:
341. Transform the raw data into a natural, conversational response.
352. Keep responses concise but informative.
363. Focus on the most relevant information.
374. Use appropriate context from the user's question.
385. Avoid simply repeating the raw data.
39
40Always use **'Actor'**, not 'actor'. Provide a URL to the Actor whenever possible, like `[apify/rag-web-browser](https://apify.com/apify/rag-web-browser)`.
41
42## Notes
43
44The server limits the number of results returned, but you can always request more results from paginated datasets or fetch additional data from the key-value store if needed.
45""",
46    "modelMaxOutputTokens": 2048,
47    "maxNumberOfToolCallsPerQuery": 20,
48    "toolCallTimeoutSec": 300,
49}
50
51# Run the Actor and wait for it to finish
52run = client.actor("drobnikj/tester-mcp-client").call(run_input=run_input)
53
54# Fetch and print Actor results from the run's dataset (if there are any)
55print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
56for item in client.dataset(run["defaultDatasetId"]).iterate_items():
57    print(item)
58
59# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Tester Mcp Client API in Python

The Apify API client for Python is the official library that allows you to use Tester Mcp Client API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Tester Mcp Client API in JavaScript

Tester Mcp Client API through CLI

Tester Mcp Client OpenAPI definition

Tester Mcp Client API

My MCP Actor

ruly_villa/my-mcp-actor

Zuzana Štětinová

Readme Video tester

fundamental_bee/my-actor-4

hanz33

mcp template

ruly_villa/mcp-template

Zuzana Štětinová

Apify Mcp Server

jakub.kopecky/apify-mcp-server

Jakub Kopecký

Actors MCP Server (Clone)

jiri.spilka/actors-mcp-server-v3

Connect Apify Actors to AI applications (AI Agents) using Anthropic's Model Context Protocol (MCP). This MCP server provides integration of any Apify Actor through the MCP framework.

Jiří Spilka

Proxy tester

mihails_staging/proxy-tester

df89 as76f89 d76as 89f 6d98sa f879d sa

Mihails

RAG Web Browser

apify/rag-web-browser

Web browser for OpenAI Assistants, RAG pipelines, or AI agents, similar to a web browser in ChatGPT. It queries Google Search, scrapes the top N pages, and returns their content as Markdown for further processing by an LLM. It can also scrape individual URLs. Supports Model Context Protocol (MCP).