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Connect AI agents to real data. MCP Nexus runs tools that fetch, extract, summarize, classify and crawl web content with caching, multi LLM support, HMAC webhooks, circuit breakers and full observability in a stateless production ready Apify actor.
You can access the MCP Nexus Universal AI Tool Bridge 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 "mode": "single",10 "tool": "fetch_web",11 "fetchUrl": "https://example.com",12 "classifyLabels": [13 "positive",14 "negative",15 "neutral",16 ],17 "extractStructuredSchema": {18 "type": "object",19 "properties": {20 "title": { "type": "string" },21 "price": { "type": "number" },22 "description": { "type": "string" },23 },24 "required": ["title"],25 },26 "batchCalls": [{27 "tool": "fetch_web",28 "params": { "url": "https://example.com" },29 }],30}31
32# Run the Actor and wait for it to finish33run = client.actor("tuguidragos/mcp-nexus-universal-ai-tool-bridge").call(run_input=run_input)34
35# Fetch and print Actor results from the run's dataset (if there are any)36print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])37for item in client.dataset(run["defaultDatasetId"]).iterate_items():38 print(item)39
40# 📚 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 MCP Nexus Universal AI Tool Bridge API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
$pip install apify-clientOther API clients include: