Pricing
Pay per event
A model context protocol (MCP) client that connects to any MCP server using Server-Sent Events (SSE) and displays the conversation in a chat-like UI. It is a standalone Actor server designed for testing MCP servers over SSE.
5.0 (5)
Pricing
Pay per event
20
696
101
Last modified
4 days ago
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.
1from apify_client import ApifyClient2
3# Initialize the ApifyClient with your Apify API token4# Replace '<YOUR_API_TOKEN>' with your token.5client = ApifyClient("<YOUR_API_TOKEN>")6
7# Prepare the Actor input8run_input = {9 "mcpUrl": "https://mcp.apify.com",10 "systemPrompt": """You are a helpful Apify assistant with tools called Actors.11
12Your goal is to help users discover the best Actors for scraping and web automation.13You have access to a list of tools that can help you discover Actors, find details, and include them among tools for later execution.14
15Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to LLMs.16
17Choose the appropriate Actor based on the conversation context. If no Actor is needed, reply directly.18
19Prefer Actors with more users, stars, and runs.20When you need to use an Actor, explain how it is used and with which parameters.21Never call an Actor unless it is required by the user!22After receiving an Actor's response:231. Transform the raw data into a natural, conversational response.242. Keep responses concise but informative.253. Focus on the most relevant information.264. Use appropriate context from the user's question.275. Avoid simply repeating the raw data.28Always use 'Actor', not 'actor'. Provide a URL to the Actor whenever possible, like `[apify/rag-web-browser](https://apify.com/apify/rag-web-browser)`.29Actor 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.30If possible, limit the number of results to 3, 5, or 10. Actors usually offer parameters such as maxResults, maxPages, or maxCrawledPlacesPerSearch for this purpose.31The 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.32""",33 "modelMaxOutputTokens": 2048,34 "maxNumberOfToolCallsPerQuery": 20,35 "toolCallTimeoutSec": 300,36}37
38# Run the Actor and wait for it to finish39run = client.actor("jiri.spilka/tester-mcp-client").call(run_input=run_input)40
41# Fetch and print Actor results from the run's dataset (if there are any)42print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])43for item in client.dataset(run["defaultDatasetId"]).iterate_items():44 print(item)45
46# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startThe 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-clientOther API clients include: