# Bitscale MCP (`team_bitscale/bitscale-mcp`) Actor

Connect AI agents to Bitscale for GTM data enrichment, research, and workflow automation.

- **URL**: https://apify.com/team\_bitscale/bitscale-mcp.md
- **Developed by:** [Bitscale MCP](https://apify.com/team_bitscale) (community)
- **Categories:** Agents, MCP servers, Automation
- **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 server template

A template for running and monetizing a [Model Context Protocol](https://modelcontextprotocol.io) server using [stdio](https://modelcontextprotocol.io/docs/concepts/transports#standard-input%2Foutput-stdio) transport on [Apify platform](https://docs.apify.com/platform).
This allows you to run any stdio MCP server as a [standby Actor](https://docs.apify.com/platform/actors/development/programming-interface/standby) and connect via either the [streamable HTTP transport](https://modelcontextprotocol.io/specification/2025-06-18/basic/transports#streamable-http) with an [MCP client](https://modelcontextprotocol.io/clients).

### How to use

Change the `MCP_COMMAND` to spawn your stdio MCP server in `src/main.ts`, and don't forget to install the required MCP server in the `package.json` (using `npm install ...`).
By default, this template runs an [Everything MCP Server](https://github.com/modelcontextprotocol/servers/tree/main/src/everything) using the following command:

```
const MCP_COMMAND = [
    'npx',
    '@modelcontextprotocol/server-everything',
];
```

Alternatively, you can use the [`mcp-remote`](https://www.npmjs.com/package/mcp-remote) tool to turn a remote MCP server into an Actor. For example, to connect to a remote server with authentication:

```
const MCP_COMMAND = [
    'npx',
    'mcp-remote',
    'https://mcp.apify.com',
    '--header',
    'Authorization: Bearer TOKEN',
];
```

Feel free to configure billing logic in `.actor/pay_per_event.json` and `src/billing.ts`.

[Push your Actor](https://docs.apify.com/academy/deploying-your-code/deploying) to the Apify platform, configure [standby mode](https://docs.apify.com/platform/actors/development/programming-interface/standby), and then connect to the Actor standby URL with your MCP client using the endpoint: `https://me--my-mcp-server.apify.actor/mcp` ([streamable HTTP transport](https://modelcontextprotocol.io/specification/2025-06-18/basic/transports#streamable-http)).

**Important:** When connecting to your deployed MCP server, you must pass your Apify API token in the `Authorization` header as a Bearer token. For example:

```
Authorization: Bearer <YOUR_APIFY_API_TOKEN>
```

This is required for authentication and to access your Actor endpoint.

#### Pay per event

This template uses the [Pay Per Event (PPE)](https://docs.apify.com/platform/actors/publishing/monetize#pay-per-event-pricing-model) monetization model, which provides flexible pricing based on defined events.

To charge users, define events in JSON format and save them on the Apify platform. Here is an example schema with the `tool-request` event:

```json
[
    {
        "tool-request": {
            "eventTitle": "Price for completing a tool request",
            "eventDescription": "Flat fee for completing a tool request.",
            "eventPriceUsd": 0.05
        }
    }
]
```

In the Actor, trigger the event with:

```typescript
await Actor.charge({ eventName: 'tool-request' });
```

This approach allows you to programmatically charge users directly from your Actor, covering the costs of execution and related services.

To set up the PPE model for this Actor:

- **Configure Pay Per Event**: establish the Pay Per Event pricing schema in the Actor's **Monetization settings**. First, set the **Pricing model** to `Pay per event` and add the schema. An example schema can be found in [pay\_per\_event.json](.actor/pay_per_event.json).

### Resources

- [What is Anthropic's Model Context Protocol?](https://blog.apify.com/what-is-model-context-protocol/)
- [How to use MCP with Apify Actors](https://blog.apify.com/how-to-use-mcp/)
- [Apify MCP server](https://mcp.apify.com)
- [Apify MCP server documentation](https://docs.apify.com/platform/integrations/mcp)
- [Apify MCP client](https://apify.com/jiri.spilka/tester-mcp-client)
- [Model Context Protocol documentation](https://modelcontextprotocol.io)
- [TypeScript tutorials in Academy](https://docs.apify.com/academy/node-js)
- [Apify SDK documentation](https://docs.apify.com/sdk/js/)

### Getting started

For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-at-apify-console). In short, you will:

1. Build the Actor
2. Run the Actor

### Pull the Actor for local development

If you would like to develop locally, you can pull the existing Actor from Apify console using Apify CLI:

1. Install `apify-cli`

   **Using Homebrew**

   ```bash
   brew install apify-cli
   ```

   **Using NPM**

   ```bash
   npm -g install apify-cli
   ```

2. Pull the Actor by its unique `<ActorId>`, which is one of the following:

   - unique name of the Actor to pull (e.g. "apify/hello-world")
   - or ID of the Actor to pull (e.g. "E2jjCZBezvAZnX8Rb")

   You can find both by clicking on the Actor title at the top of the page, which will open a modal containing both Actor unique name and Actor ID.

   This command will copy the Actor into the current directory on your local machine.

   ```bash
   apify pull <ActorId>
   ```

### Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

# Actor input Schema

## Actor input object example

```json
{}
```

# 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("team_bitscale/bitscale-mcp").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("team_bitscale/bitscale-mcp").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 team_bitscale/bitscale-mcp --silent --output-dataset

```

## MCP server setup

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

```

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/bhDgdDWgT1JScstmd/builds/0WQhzrrJsicP7qbVO/openapi.json