# MCP.so Server Directory Scraper (`jungle_synthesizer/mcp-so-server-directory-scraper`) Actor

Scrape the complete MCP.so server directory — the 3rd canonical MCP registry alongside Smithery and Glama. Extracts server name, author, category, tags, capabilities, install command, GitHub repo URL, README, and more for every listed MCP server.

- **URL**: https://apify.com/jungle\_synthesizer/mcp-so-server-directory-scraper.md
- **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community)
- **Categories:** Developer tools, Business
- **Stats:** 2 total users, 1 monthly users, 69.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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/platform/actors/running/actors-in-store#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.so Server Directory Scraper

Scrape the complete [MCP.so](https://mcp.so/) server directory — the 3rd canonical MCP registry alongside Smithery and Glama. Extracts name, author, category, tags, capabilities, tool count, install command, GitHub repo URL, README markdown, and more for every listed MCP server.

### What does it scrape?

MCP.so is one of the top-3 community indexes for Model Context Protocol (MCP) servers — the protocol used by Claude Desktop, Cursor, Windsurf, and Codex to connect AI models to external tools. This scraper enumerates every server in the directory and returns a structured record per entry.

#### Data fields returned

| Field | Description |
|-------|-------------|
| `server_id` | Unique identifier in `<slug>/<author>` format |
| `server_name` | Display name of the MCP server |
| `server_slug` | URL slug |
| `author_username` | GitHub username of the author |
| `author_avatar_url` | Author avatar image URL |
| `tagline` | Short description |
| `description` | Full description |
| `category` | Category (databases, developer-tools, etc.) |
| `tags` | Comma-separated tags |
| `capabilities` | MCP capability types present (tools, resources, prompts) |
| `tool_count` | Number of MCP tools exposed |
| `install_command` | npx / uvx / docker installation command |
| `npm_package` | NPM package name (if applicable) |
| `pypi_package` | PyPI package name (if applicable) |
| `docker_image` | Docker image name (if applicable) |
| `github_repo` | GitHub repository URL |
| `is_official` | Whether this is an official MCP team server |
| `is_verified` | Whether marked as featured/verified |
| `listed_at` | Date first listed on mcp.so |
| `updated_at` | Last update timestamp |
| `readme_markdown` | Full README content |
| `profile_url` | URL of the mcp.so server page |
| `scraped_at` | Scrape timestamp |

### Usage

Set `maxItems` to limit the number of servers returned. The directory has ~2,000 servers across two sitemaps.

#### Input

```json
{
  "maxItems": 100
}
```

#### Output sample

```json
{
  "server_id": "redis/modelcontextprotocol",
  "server_name": "Redis",
  "server_slug": "redis",
  "author_username": "modelcontextprotocol",
  "category": "databases",
  "tags": null,
  "capabilities": "tools",
  "tool_count": 13,
  "install_command": "docker run -i --rm mcp/redis {redis_url}",
  "docker_image": "mcp/redis",
  "github_repo": "https://github.com/modelcontextprotocol/servers/tree/main/src/redis",
  "is_official": false,
  "is_verified": false,
  "listed_at": null,
  "profile_url": "https://mcp.so/servers/redis"
}
```

### Triple MCP Coverage

This scraper completes our 3-index MCP directory coverage:

| Registry | Actor |
|----------|-------|
| Smithery | `jungle_synthesizer/smithery-mcp-registry-scraper` |
| Glama | `jungle_synthesizer/glama-mcp-registry-scraper` |
| MCP.so | This actor |

Use all three to build an exhaustive MCP server catalog for agent platform development, ecosystem analysis, or security research.

### Notes on data availability

mcp.so migrated its front-end to TanStack Start (2026-07, FR 480), which changed both the sitemap shape (`/sitemap.xml` index → `?section=servers&page=N` children) and the detail-page URL shape (`/server/<slug>/<author>` → `/servers/<slug>`). Structured data is now sourced from the page's JSON-LD `SoftwareApplication` block plus the rendered install-config code block and tools accordion, rather than the old embedded RSC payload.

As a result the following fields are no longer exposed by mcp.so and will always be `null`/`false` in every record: `tags`, `resource_count`, `prompt_count`, `github_stars`, `github_forks`, `language`, `license`, `view_count`, `install_count`, `listed_at`, `updated_at`, `documentation_url`, `is_official`, `is_verified` (`is_official`/`is_verified` are always `false` — there is no longer a reliable official/verified signal on the detail page). `github_stars`, `github_forks`, `language`, and `license` would require GitHub API enrichment as a separate step.

# Actor input Schema

## `sp_intended_usage` (type: `string`):

What will this data feed? E.g. lead lists, KYB checks, price tracking.

## `sp_improvement_suggestions` (type: `string`):

Provide any feedback or suggestions for improvements.

## `sp_contact` (type: `string`):

We'll personally help with your use case. No spam.

## `resumeCursor` (type: `string`):

Leave empty for a fresh crawl. To CONTINUE a previous run where it stopped — without paying again for records you already received — paste the `resumeCursor` value from that run's Output (the run's OUTPUT key). Resume promptly: the previous run's data expires with your account's retention window (free tier: your ~10 most recent runs).

## `maxItems` (type: `integer`):

Maximum number of records to scrape

## Actor input object example

```json
{
  "sp_intended_usage": "Describe your intended use...",
  "sp_improvement_suggestions": "Share your suggestions here...",
  "sp_contact": "Share your email here...",
  "maxItems": 5
}
```

# Actor output Schema

## `results` (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 = {
    "sp_intended_usage": "Describe your intended use...",
    "sp_improvement_suggestions": "Share your suggestions here...",
    "sp_contact": "Share your email here...",
    "maxItems": 5
};

// Run the Actor and wait for it to finish
const run = await client.actor("jungle_synthesizer/mcp-so-server-directory-scraper").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 = {
    "sp_intended_usage": "Describe your intended use...",
    "sp_improvement_suggestions": "Share your suggestions here...",
    "sp_contact": "Share your email here...",
    "maxItems": 5,
}

# Run the Actor and wait for it to finish
run = client.actor("jungle_synthesizer/mcp-so-server-directory-scraper").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 '{
  "sp_intended_usage": "Describe your intended use...",
  "sp_improvement_suggestions": "Share your suggestions here...",
  "sp_contact": "Share your email here...",
  "maxItems": 5
}' |
apify call jungle_synthesizer/mcp-so-server-directory-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=jungle_synthesizer/mcp-so-server-directory-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/eeiyMrHUm94DFLJOI/builds/iZNUfOBgIuo0yCGHC/openapi.json