# MCP Endpoint Health Monitor — Protocol & Tools Check (`plenteous_humidifier/mcp-health-monitor`) Actor

Test public Model Context Protocol endpoints beyond HTTP 200. Validate MCP discovery or initialize, JSON-RPC, Streamable HTTP, negotiated versions, tools/list, latency, and authentication boundaries in batch.

- **URL**: https://apify.com/plenteous\_humidifier/mcp-health-monitor.md
- **Developed by:** [Luigy Gabriel](https://apify.com/plenteous_humidifier) (community)
- **Categories:** AI, Developer tools, MCP servers
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## MCP Endpoint Health Monitor

An HTTP 200 is not an MCP health check. This Actor validates public Streamable HTTP endpoints at the protocol layer: JSON-RPC shape, current stateless discovery, compatibility initialization, version negotiation, tool discovery, latency, and authentication boundaries.

### Checks

- MCP 2026-07-28 `server/discover`
- Compatibility fallback to the 2025-11-25 `initialize` handshake
- JSON-RPC 2.0 response validity
- `tools/list` and discovered tool names
- HTTP status and aggregate latency
- Clear `auth-required`, `degraded`, `unreachable`, and `invalid` states

### Security boundaries

Version 1 accepts unauthenticated public HTTP(S) endpoints only. It rejects credentials embedded in URLs and blocks DNS targets that resolve to private, loopback, link-local, benchmark, multicast, or metadata-network ranges. Redirects are not followed.

### Automation

Add up to 50 endpoints, schedule the Actor in Apify, and connect the dataset or webhook to your monitoring workflow. Each endpoint produces one structured dataset item; the complete run summary is stored in the `REPORT` key-value record.

# Actor input Schema

## `endpoints` (type: `array`):

Public Streamable HTTP endpoint URLs. Authentication headers are intentionally excluded from version 1.

## `timeoutMs` (type: `integer`):

Maximum time to wait for each protocol request.

## `concurrency` (type: `integer`):

Number of endpoint checks to run at the same time.

## Actor input object example

```json
{
  "endpoints": [
    {
      "name": "My MCP server",
      "url": "https://example.com/mcp"
    }
  ],
  "timeoutMs": 10000,
  "concurrency": 5
}
```

# Actor output Schema

## `checks` (type: `string`):

No description

## `report` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("plenteous_humidifier/mcp-health-monitor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("plenteous_humidifier/mcp-health-monitor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call plenteous_humidifier/mcp-health-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=plenteous_humidifier/mcp-health-monitor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/9UeC7MfByf3iZisVF/builds/7xn7zF9U0YMAf28wa/openapi.json