MCP Schema Policy Linter
Pricing
from $50.00 / 1,000 policy report createds
Go to Apify Store
MCP Schema Policy Linter
Lint an MCP connector against the public 2024-11-05 JSON Schema. Static check, not a runtime sandbox. $0.05 / report.
MCP Schema Policy Linter
Pricing
from $50.00 / 1,000 policy report createds
Lint an MCP connector against the public 2024-11-05 JSON Schema. Static check, not a runtime sandbox. $0.05 / report.
You can access the MCP Schema Policy Linter 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 API & Integrations 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 "searchKeywords": [10 "source-backed signal",11 "buyer fit",12 ],13 "taskIntent": "buyer-ready-product-run",14 "sourceMode": "startUrls",15 "outputMode": "buyer-ready-records",16 "startUrls": [],17 "requestTimeoutSecs": 30,18 "maxRequestRetries": 2,19 "sinceLastRun": False,20 "deltaMode": True,21}22
23# Run the Actor and wait for it to finish24run = client.actor("zentrafoundry/zentra-mcp-connector-policy-linter").call(run_input=run_input)25
26# Fetch and print Actor results from the run's dataset (if there are any)27print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")28for item in client.dataset(run.default_dataset_id).iterate_items():29 print(item)30
31# 📚 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 Schema Policy Linter API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
$pip install apify-clientOther API clients include: