# SPSS MCP Full Control (`mai_amm/spss-mcp-full-control`) Actor

Run SPSS-oriented analysis workflows through an MCP bridge from any MCP-capable AI client or Apify workflow.

- **URL**: https://apify.com/mai\_amm/spss-mcp-full-control.md
- **Developed by:** [wiseld\_squid](https://apify.com/mai_amm) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1,990.00 / 1,000 successful spss workflows

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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use 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

## SPSS MCP Full Control

This project is a full-scope MCP front end for IBM SPSS Statistics automation.

It is designed for the architecture that actually fits SPSS:

1. IBM SPSS Statistics runs on a desktop, VM, Windows server, or batch host.
2. A local bridge beside SPSS owns the real SPSS session, executes procedures, tracks the active dataset, and captures output artifacts.
3. This MCP server exposes a broad tool surface to AI clients.
4. Any MCP-capable AI client connects to this MCP server and can drive SPSS through structured tools.

Compatible client targets include Claude Desktop, Cursor, VS Code MCP, Copilot-style MCP clients, OpenAI agent runtimes with MCP support, local agent frameworks, n8n/Make HTTP flows, and custom apps that can call the Apify Actor API.

This repository does not pretend Apify or cloud containers should directly host desktop SPSS.
It assumes a proper execution bridge next to the licensed SPSS environment.

### What This Actor Does

- gives AI agents a clean SPSS workflow interface
- orchestrates SPSS bridge calls from Apify
- generates MCP connection guidance
- runs structured analysis goals such as exploration, group comparison, regression, survey analysis, and forecasting
- records workflow results, summaries, and artifacts in Apify storage

### What This Actor Does Not Include

- an IBM SPSS Statistics license
- hosted desktop SPSS inside Apify
- guaranteed access to private datasets unless your bridge can reach them
- final statistical judgment without user review

### Scope

This is not an MVP-shaped tool list. The server surface is intentionally broad:

- session lifecycle
- dataset lifecycle
- variable inspection
- data transformation
- missing-value handling
- descriptive statistics
- crosstabs and group comparisons
- regression
- factor and cluster analysis
- forecasting
- reviewed or raw syntax execution
- export, explanation, and report generation

### Why this shape

People use SPSS for a predictable set of workflows:

- clean data
- inspect variables
- run descriptive stats
- test group differences
- model relationships
- analyze surveys and segments
- build forecasts
- export and interpret results

The MCP server should map to those jobs directly instead of exposing only a generic `run syntax` escape hatch.

### Policy model

Full control does not mean no guardrails.

- `allowWrite=false` by default
- `allowRawSyntax=false` by default
- write actions and raw syntax should be enabled only for trusted contexts
- the bridge should maintain audit logs, file path restrictions, and session history

### Current state

This repository contains:

- a real MCP server for `stdio` and `Streamable HTTP`
- a broad SPSS tool surface
- a runtime policy layer
- a Python bridge skeleton that starts from SPSS-native concepts

What it does not yet contain:

- output parsers for `.spv`, HTML, pivot tables, or chart artifacts
- batch fallback wiring through `statisticsb`
- approval workflows and auth

### Suggested bridge implementation

Run the bridge on the machine that has SPSS access. The bridge should implement actions such as:

- `start_session`
- `stop_session`
- `list_outputs`
- `list_datasets`
- `open_dataset`
- `describe_dataset`
- `inspect_variables`
- `compute_variable`
- `recode_variable`
- `filter_cases`
- `merge_files`
- `handle_missing`
- `frequencies`
- `descriptives`
- `crosstabs`
- `compare_groups`
- `correlation`
- `linear_regression`
- `logistic_regression`
- `factor_analysis`
- `cluster_analysis`
- `forecast`
- `run_syntax`
- `export_output`
- `explain_output`
- `generate_report`

Each action should return structured JSON:

```json
{
  "ok": true,
  "sessionId": "abc123",
  "activeDataset": "data.sav",
  "logs": [],
  "tables": [],
  "warnings": [],
  "artifacts": [],
  "summary": {}
}
````

### Run locally

Install dependencies:

```bash
npm install
```

Start in stdio mode:

```bash
npm run mcp:stdio
```

Start in HTTP mode:

```bash
npm run mcp:http
```

### Run As An Apify Actor

The Actor layer is built for users and AI agents that do not want to think in SPSS syntax first.
They choose a goal, fill the minimum variables, and the Actor turns that into SPSS session actions.

Supported Actor goals:

- `connection_guide`: produce MCP/bridge connection instructions
- `explore_dataset`: start session, open data, describe dictionary, inspect variables
- `compare_groups`: run an automatic group-comparison workflow
- `find_relationships`: run correlation or regression depending on supplied fields
- `survey_analyzer`: run frequencies, crosstabs, and optional factor analysis
- `forecast`: run a time-series forecasting workflow
- `run_syntax`: run reviewed or raw SPSS syntax subject to policy
- `batch`: run explicit action objects for advanced users

Required production setup:

- An SPSS bridge URL reachable from Apify, usually a private server or tunnel on the machine that can run IBM SPSS Statistics.
- `authToken` configured as a secret input.
- The bridge must expose MCP tool calls for actions such as `spss_start_session`, `spss_open_dataset`, and `spss_descriptives`.

### AI Client Setup

Use the same MCP server with any AI client that supports MCP over `stdio` or Streamable HTTP.

Local stdio example:

```json
{
  "mcpServers": {
    "spss": {
      "command": "node",
      "args": ["/path/to/spss-mcp-full-control/src/server.js", "--transport", "stdio"],
      "env": {
        "SPSS_BRIDGE_URL": "http://127.0.0.1:8091",
        "SPSS_AUTH_TOKEN": "change-me"
      }
    }
  }
}
```

Remote HTTP example:

```json
{
  "mcpServers": {
    "spss": {
      "url": "https://your-spss-mcp.example.com/mcp",
      "headers": {
        "Authorization": "Bearer change-me"
      }
    }
  }
}
```

For AI tools without MCP, call the Apify Actor API with a `goal` such as `explore_dataset`, `compare_groups`, or `find_relationships`.

Usability rule:

The Actor should accept research-language inputs first, then produce SPSS procedure calls and artifacts. Raw syntax stays available, but it is not the main product surface.

### SPSS-native bridge

See [bridge/spss\_bridge.py](bridge/spss_bridge.py) and [bridge/README.md](bridge/README.md).

The bridge is shaped around:

- `spss.StartSPSS()`
- `spss.Submit()`
- active dataset state
- output viewer history
- procedure-oriented workflows

That is the right mental model for SPSS. The MCP server is only the AI-facing control plane.

# Actor input Schema

## `bridgeUrl` (type: `string`):

Base URL of your SPSS MCP bridge running beside IBM SPSS Statistics. Leave empty to generate a dry-run plan.

## `authToken` (type: `string`):

Bearer token for the SPSS bridge. Store as a secret input on Apify.

## `goal` (type: `string`):

Choose the SPSS job you want the Actor to perform.

## `sessionId` (type: `string`):

Optional SPSS session ID. Leave empty to let the bridge create or use its default session.

## `datasetPath` (type: `string`):

Path or mounted location of a .sav/.zsav/.por/.csv file that the SPSS bridge can access.

## `dataset` (type: `string`):

Optional logical dataset name inside the SPSS session.

## `variables` (type: `array`):

Variables for exploration, frequencies, correlations, or survey analysis.

## `outcomeVariable` (type: `string`):

Dependent or outcome variable for comparison workflows.

## `groupVariable` (type: `string`):

Grouping variable for t-test, ANOVA, chi-square, or other comparisons.

## `dependent` (type: `string`):

Dependent variable for regression.

## `independents` (type: `array`):

Predictor variables for regression.

## `modelType` (type: `string`):

Regression model type for relationship analysis.

## `rowVariable` (type: `string`):

Row variable for crosstabs.

## `columnVariable` (type: `string`):

Column variable for crosstabs.

## `scaleVariables` (type: `array`):

Scale items for factor analysis in survey workflows.

## `timeVariable` (type: `string`):

Date or time variable for forecasting.

## `targetVariable` (type: `string`):

Metric to forecast.

## `horizon` (type: `integer`):

Number of future periods to forecast.

## `syntax` (type: `string`):

SPSS syntax for run\_syntax mode.

## `syntaxMode` (type: `string`):

Reviewed syntax is allowed when write policy permits syntax. Raw syntax requires allowRawSyntax.

## `commands` (type: `array`):

Advanced list of action objects for batch mode.

## `exportFormat` (type: `string`):

Optional export format after the workflow finishes.

## `generateReport` (type: `boolean`):

Generate a report package after running the workflow.

## `reportStyle` (type: `string`):

Report style for generated reports.

## `allowWrite` (type: `boolean`):

Allow compute, recode, filter, merge, missing-value transformation, and syntax actions.

## `allowRawSyntax` (type: `boolean`):

Allow raw syntax execution. Use only for trusted bridge environments.

## `autoStartSession` (type: `boolean`):

Start an SPSS session before the workflow.

## `stopOnError` (type: `boolean`):

Stop batch execution after the first failed command.

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

HTTP timeout for each bridge request.

## Actor input object example

```json
{
  "goal": "explore_dataset",
  "modelType": "linear",
  "syntaxMode": "reviewed",
  "generateReport": false,
  "reportStyle": "technical",
  "allowWrite": false,
  "allowRawSyntax": false,
  "autoStartSession": true,
  "stopOnError": true,
  "timeoutSecs": 120
}
```

# Actor output Schema

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

Normalized SPSS action results.

## `summary` (type: `string`):

Run-level status and counts.

## `output` (type: `string`):

Compact output object with summary and result statuses.

# 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("mai_amm/spss-mcp-full-control").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("mai_amm/spss-mcp-full-control").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 mai_amm/spss-mcp-full-control --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "SPSS MCP Full Control",
        "description": "Run SPSS-oriented analysis workflows through an MCP bridge from any MCP-capable AI client or Apify workflow.",
        "version": "1.0",
        "x-build-id": "RlQfk9ob3WKVYSILv"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/mai_amm~spss-mcp-full-control/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-mai_amm-spss-mcp-full-control",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/mai_amm~spss-mcp-full-control/runs": {
            "post": {
                "operationId": "runs-sync-mai_amm-spss-mcp-full-control",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/mai_amm~spss-mcp-full-control/run-sync": {
            "post": {
                "operationId": "run-sync-mai_amm-spss-mcp-full-control",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "properties": {
                    "bridgeUrl": {
                        "title": "SPSS Bridge URL",
                        "type": "string",
                        "description": "Base URL of your SPSS MCP bridge running beside IBM SPSS Statistics. Leave empty to generate a dry-run plan."
                    },
                    "authToken": {
                        "title": "Auth Token",
                        "type": "string",
                        "description": "Bearer token for the SPSS bridge. Store as a secret input on Apify."
                    },
                    "goal": {
                        "title": "Goal",
                        "enum": [
                            "connection_guide",
                            "explore_dataset",
                            "compare_groups",
                            "find_relationships",
                            "survey_analyzer",
                            "forecast",
                            "run_syntax",
                            "batch"
                        ],
                        "type": "string",
                        "description": "Choose the SPSS job you want the Actor to perform.",
                        "default": "explore_dataset"
                    },
                    "sessionId": {
                        "title": "Session ID",
                        "type": "string",
                        "description": "Optional SPSS session ID. Leave empty to let the bridge create or use its default session."
                    },
                    "datasetPath": {
                        "title": "Dataset Path",
                        "type": "string",
                        "description": "Path or mounted location of a .sav/.zsav/.por/.csv file that the SPSS bridge can access."
                    },
                    "dataset": {
                        "title": "Dataset Name",
                        "type": "string",
                        "description": "Optional logical dataset name inside the SPSS session."
                    },
                    "variables": {
                        "title": "Variables",
                        "type": "array",
                        "description": "Variables for exploration, frequencies, correlations, or survey analysis.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "outcomeVariable": {
                        "title": "Outcome Variable",
                        "type": "string",
                        "description": "Dependent or outcome variable for comparison workflows."
                    },
                    "groupVariable": {
                        "title": "Group Variable",
                        "type": "string",
                        "description": "Grouping variable for t-test, ANOVA, chi-square, or other comparisons."
                    },
                    "dependent": {
                        "title": "Dependent Variable",
                        "type": "string",
                        "description": "Dependent variable for regression."
                    },
                    "independents": {
                        "title": "Independent Variables",
                        "type": "array",
                        "description": "Predictor variables for regression.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "modelType": {
                        "title": "Model Type",
                        "enum": [
                            "linear",
                            "logistic"
                        ],
                        "type": "string",
                        "description": "Regression model type for relationship analysis.",
                        "default": "linear"
                    },
                    "rowVariable": {
                        "title": "Row Variable",
                        "type": "string",
                        "description": "Row variable for crosstabs."
                    },
                    "columnVariable": {
                        "title": "Column Variable",
                        "type": "string",
                        "description": "Column variable for crosstabs."
                    },
                    "scaleVariables": {
                        "title": "Scale Variables",
                        "type": "array",
                        "description": "Scale items for factor analysis in survey workflows.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "timeVariable": {
                        "title": "Time Variable",
                        "type": "string",
                        "description": "Date or time variable for forecasting."
                    },
                    "targetVariable": {
                        "title": "Target Variable",
                        "type": "string",
                        "description": "Metric to forecast."
                    },
                    "horizon": {
                        "title": "Forecast Horizon",
                        "minimum": 1,
                        "maximum": 1000,
                        "type": "integer",
                        "description": "Number of future periods to forecast."
                    },
                    "syntax": {
                        "title": "SPSS Syntax",
                        "type": "string",
                        "description": "SPSS syntax for run_syntax mode."
                    },
                    "syntaxMode": {
                        "title": "Syntax Mode",
                        "enum": [
                            "reviewed",
                            "raw"
                        ],
                        "type": "string",
                        "description": "Reviewed syntax is allowed when write policy permits syntax. Raw syntax requires allowRawSyntax.",
                        "default": "reviewed"
                    },
                    "commands": {
                        "title": "Batch Commands",
                        "type": "array",
                        "description": "Advanced list of action objects for batch mode."
                    },
                    "exportFormat": {
                        "title": "Export Format",
                        "enum": [
                            "html",
                            "pdf",
                            "csv",
                            "xlsx",
                            "sav",
                            "spv"
                        ],
                        "type": "string",
                        "description": "Optional export format after the workflow finishes."
                    },
                    "generateReport": {
                        "title": "Generate Report",
                        "type": "boolean",
                        "description": "Generate a report package after running the workflow.",
                        "default": false
                    },
                    "reportStyle": {
                        "title": "Report Style",
                        "enum": [
                            "executive",
                            "technical",
                            "academic"
                        ],
                        "type": "string",
                        "description": "Report style for generated reports.",
                        "default": "technical"
                    },
                    "allowWrite": {
                        "title": "Allow Data-Mutating Actions",
                        "type": "boolean",
                        "description": "Allow compute, recode, filter, merge, missing-value transformation, and syntax actions.",
                        "default": false
                    },
                    "allowRawSyntax": {
                        "title": "Allow Raw Syntax",
                        "type": "boolean",
                        "description": "Allow raw syntax execution. Use only for trusted bridge environments.",
                        "default": false
                    },
                    "autoStartSession": {
                        "title": "Auto Start Session",
                        "type": "boolean",
                        "description": "Start an SPSS session before the workflow.",
                        "default": true
                    },
                    "stopOnError": {
                        "title": "Stop On Error",
                        "type": "boolean",
                        "description": "Stop batch execution after the first failed command.",
                        "default": true
                    },
                    "timeoutSecs": {
                        "title": "Request Timeout Seconds",
                        "minimum": 1,
                        "maximum": 3600,
                        "type": "integer",
                        "description": "HTTP timeout for each bridge request.",
                        "default": 120
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```