# MCP Server Probe (`conserving_mastodon/mcp-server-probe`) Actor

Handshake, tool inventory, and latency for any Model Context Protocol server over streamable HTTP: server info, capabilities, every tool with its input schema, session mode, auth behavior. Charged only when a probe completes.

- **URL**: https://apify.com/conserving\_mastodon/mcp-server-probe.md
- **Developed by:** [Chris Arsenault](https://apify.com/conserving_mastodon) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$150.00 / 1,000 completed probes

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## 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 Server Probe

**Point it at any Model Context Protocol endpoint and get the full picture in one call:** does it speak MCP, what server is it, which protocol version, what capabilities does it declare, how fast does it initialize, does it manage sessions, does it need auth, and — the part you actually came for — **every tool it exposes, with each tool's description, input properties, and required fields.**

### Why this exists

The MCP ecosystem is growing faster than anyone can evaluate it. Before an agent adopts a server (or before you list a dependency on one), someone has to answer: is this endpoint real, healthy, and what exactly can it do? Doing that by hand means writing the initialize/initialized/tools-list handshake yourself. This Actor is that handshake, productized.

We built it because we run our own public MCP server and needed to verify it from the outside, the way a stranger's agent would see it.

### What you get

A **summary row**:

```json
{
  "ok": true,
  "url": "https://gozerai.com/mcp/library",
  "server_name": "1450 Library",
  "protocol_version": "2025-06-18",
  "initialize_latency_ms": 456,
  "session_managed": true,
  "capabilities": ["prompts", "resources", "tools"],
  "tools_count": 3
}
```

Plus **one row per tool**:

```json
{
  "name": "search_library",
  "description": "Search a curated library of practical small-business guides...",
  "input_properties": ["query", "limit"],
  "required": ["query"]
}
```

### Input

| Field | Type | Description |
|---|---|---|
| `url` | string | The MCP streamable HTTP endpoint |
| `bearerToken` | string, optional | Sent as `Authorization: Bearer` for authenticated servers |
| `timeoutSecs` | integer | Per-request timeout, default 30 |

### Behavior and honesty

- Speaks the streamable HTTP transport (JSON and SSE responses both handled), protocol `2025-06-18`.
- A non-MCP endpoint, an auth wall you did not provide a token for, or a dead server produces a clean `ok: false` row with the reason, and **you are not charged**. Billing is per completed probe.
- Read-only by construction: it initializes, lists, and leaves. It never calls the server's tools.

### Use cases

- **Agent builders** vetting third-party MCP servers before wiring them in.
- **Server authors** monitoring their own endpoint from outside (schedule it; alert if `ok` flips or latency spikes).
- **Directories and researchers** inventorying what a set of MCP endpoints actually expose.

Built and used daily by 1450 Enterprises — this probe's first production target was our own public library server.

# Actor input Schema

## `url` (type: `string`):

Streamable HTTP endpoint of the MCP server (e.g. https://example.com/mcp).

## `bearerToken` (type: `string`):

Sent as Authorization: Bearer for servers that require auth.

## `timeoutSecs` (type: `integer`):

Per-request timeout for each protocol call.

## Actor input object example

```json
{
  "url": "https://gozerai.com/mcp/library",
  "timeoutSecs": 30
}
```

# Actor output Schema

## `results` (type: `string`):

First row: server info, protocol version, capabilities, latency, counts. Subsequent rows: each tool with its description, input properties, and required fields.

# 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 = {
    "url": "https://gozerai.com/mcp/library"
};

// Run the Actor and wait for it to finish
const run = await client.actor("conserving_mastodon/mcp-server-probe").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 = { "url": "https://gozerai.com/mcp/library" }

# Run the Actor and wait for it to finish
run = client.actor("conserving_mastodon/mcp-server-probe").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 '{
  "url": "https://gozerai.com/mcp/library"
}' |
apify call conserving_mastodon/mcp-server-probe --silent --output-dataset

```

## MCP server setup

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

```

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/MYfFq5GO6b5nZVxTI/builds/fCf9thgSsaOBMqnI5/openapi.json