# BLS CPI MCP — Consumer Price Index by Category (`andrew_avina/bls-cpi-mcp`) Actor

BLS CPI MCP — Consumer Price Index by Category

- **URL**: https://apify.com/andrew\_avina/bls-cpi-mcp.md
- **Developed by:** [Andrew Avina](https://apify.com/andrew_avina) (community)
- **Categories:** MCP servers, Business
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.50 / 1,000 result item returneds

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

## BLS CPI MCP — Consumer Price Index by Category & Time Period

### Overview

The Consumer Price Index (CPI), published by the U.S. Bureau of Labor Statistics (BLS), measures the average change over time in the prices paid by urban consumers for a representative basket of goods and services. This actor fetches monthly CPI data directly from the BLS public API v2 and surfaces it as structured records ready for downstream analysis, modeling, or MCP tool consumption.

### Features

- **Category filtering** — query one focused category or pull all items together
- **Supported categories**: `food`, `energy`, `shelter`, `medical`, `apparel`, `all`
- **Monthly granularity** — each record represents one calendar month
- **2-year default range** — sensible out-of-the-box window (2022–2024)
- **Automatic fallback** — if the BLS API is unavailable or rate-limited, the actor serves a curated set of realistic 2024 CPI values so downstream consumers never receive an empty dataset

### Input

```json
{
  "category":   "food",
  "start_year": 2022,
  "end_year":   2024,
  "limit":      20
}
```

| Field        | Type    | Default | Options                                      |
|--------------|---------|---------|----------------------------------------------|
| `category`   | string  | `"all"` | `food`, `energy`, `shelter`, `apparel`, `medical`, `all` |
| `start_year` | integer | `2022`  | Any year supported by BLS API                |
| `end_year`   | integer | `2024`  | Must be >= `start_year`                      |
| `limit`      | integer | `20`    | Max records to push across all series        |

### Output

Each record in the dataset contains exactly 8 fields:

| Field         | Type    | Description                                         |
|---------------|---------|-----------------------------------------------------|
| `series_id`   | string  | BLS series identifier (e.g. `CUUR0000SAF1`)        |
| `series_name` | string  | Human-readable series label (e.g. `"Food"`)        |
| `category`    | string  | Input category used for the query                   |
| `period`      | string  | BLS period code (e.g. `"M01"` for January)         |
| `year`        | integer | Calendar year of the data point                     |
| `month`       | integer | Calendar month as an integer (1–12)                 |
| `value`       | float   | CPI index value (base period 1982-84=100)           |
| `base_period` | string  | Always `"1982-84=100"` — standard BLS CPI base     |

### Use Cases

- **Inflation analysis** — track month-over-month and year-over-year price changes across consumer categories
- **Cost modeling** — incorporate real CPI trends into financial projections and scenario planning
- **Wage adjustment calculations** — compute cost-of-living adjustments (COLA) for compensation reviews
- **Contract indexing** — benchmark escalation clauses in long-term service or supply agreements to official government price indices

## 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("andrew_avina/bls-cpi-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("andrew_avina/bls-cpi-mcp").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 andrew_avina/bls-cpi-mcp --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/0knKqT111RyvV9lcJ/builds/ME0XhmExOw3pj9RMU/openapi.json