# Relvato MCP Server: website monitoring for AI agents (`relvato/relvato-mcp-server`) Actor

Connect AI agents to Relvato, the website monitoring platform: check how a site is doing, see what broke and why, get the fix brief for a failed run, and start scans. Uses your own Relvato account and API key.

- **URL**: https://apify.com/relvato/relvato-mcp-server.md
- **Developed by:** [Relvato](https://apify.com/relvato) (community)
- **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/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Relvato MCP Server

Connect your AI agent to [Relvato](https://www.relvato.com), the website monitoring platform. Ask how a site is doing, see what broke and why, get the fix brief for a failed run, and start a scan, from any MCP client.

Relvato runs real-browser and server-side monitors against your sites: uptime, SSL, checkout, login, forms, broken links, visual changes, Core Web Vitals, SEO, security and legal pages. It re-runs them after updates. This Actor connects an agent to **your own Relvato account**, through Relvato's official MCP server.

### What your agent can do

- List your sites and the latest result of every monitor.
- Explain a failure: what the monitor saw, what changed before it, and the fix brief for the run.
- With your approval: add a site or monitors, change schedules, start a scan, ignore a finding you accept.
- Read performance, uptime, updates, activity and alert settings.

58 tools in all; the full list is at [relvato.com/developers](https://www.relvato.com/developers). Deleting anything, approving security-sensitive changes, alert recipients and secrets stay in the Relvato dashboard. Relvato never changes your website remotely: fixes are applied by you, in WordPress.

### Connect

You need:

1. **A Relvato account and API key.** The free plan works. Create a key at [app.relvato.com/api-access](https://app.relvato.com/api-access). A read-only key only gets the read tools.
2. **Your Apify API token**, from [Apify Console → Integrations](https://console.apify.com/account/integrations).

MCP endpoint:

```text
https://relvato--relvato-mcp-server.apify.actor/mcp
```

Client configuration. Your Apify token goes in `Authorization`, your Relvato key in `X-Relvato-Key`:

```json
{
  "mcpServers": {
    "relvato": {
      "url": "https://relvato--relvato-mcp-server.apify.actor/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN",
        "X-Relvato-Key": "rlv_YOUR_RELVATO_KEY"
      }
    }
  }
}
```

The transport is Streamable HTTP. Then ask, for example: *"Using Relvato, how is example.com doing?"*

Not using Apify otherwise? Connect to Relvato directly at `https://app.relvato.com/api/mcp`, signing in or with the same API key. Setup for Claude, ChatGPT, Perplexity, Cursor and others is at [relvato.com/developers](https://www.relvato.com/developers).

### Privacy and security

- **Your key stays yours.** The Actor forwards it to Relvato with each request and never stores it, in Apify storage or anywhere else.
- **Your Apify token never reaches Relvato.** Only the MCP request goes on, with your Relvato key.
- **Minimal logs.** The Actor logs each request's method and Relvato's status. Never keys, tool arguments or results.
- **One account per key.** Every call is scoped to your Relvato workspace and rate-limited by your Relvato plan.

What Relvato does with data: [Trust](https://www.relvato.com/trust) and [Privacy](https://www.relvato.com/privacy).

### Pricing

The Actor itself is free. Apify bills its usual platform usage while the server runs for you. Relvato usage counts against your Relvato plan, and the free plan is enough to try it.

### Support

<contact@relvato.com> · [relvato.com/developers](https://www.relvato.com/developers) · [Status](https://www.relvato.com/status)

# Actor input Schema

## Actor input object example

```json
{}
```

# Actor output Schema

## `mcpEndpoint` (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("relvato/relvato-mcp-server").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("relvato/relvato-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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 relvato/relvato-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,relvato/relvato-mcp-server"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Vd9jTDGcz7fsMNc91/builds/Y3WqnoWVW56Mcf5yv/openapi.json