# Prague Graves (`calvera/prague-graves`) Actor

- **URL**: https://apify.com/calvera/prague-graves.md
- **Developed by:** [Karel Sommer](https://apify.com/calvera) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 results

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Prague Graves Search

Search graves in Prague cemeteries via [Správa pražských hřbitovů](http://212.47.2.130:8080/mpo_sphw/) by surname, first name, birth year, and/or death year.

### Features

- Searches the official Prague cemetery grave locator
- Optional filters: first name, birth year, death year, cemetery
- Automatically fills the site’s plain-text security code (no image CAPTCHA)
- Outputs grave location: cemetery, section, department, grave number, and office

### Input

| Field | Required | Description |
| --- | --- | --- |
| `surname` | yes | Surname of the deceased (accent-insensitive) |
| `firstName` | no | First name |
| `birthYear` | no | Birth year (4 digits; the site has no full-date fields) |
| `deathYear` | no | Death or burial year (4 digits) |
| `cemetery` | no | Cemetery ID; default `0` = all cemeteries |

Example:

```json
{
    "surname": "Masaryk"
}
```

Narrow a common surname:

```json
{
    "surname": "Novák",
    "deathYear": 1950,
    "cemetery": "20000001"
}
```

If the site returns “too many records”, add more criteria.

### Output

Each dataset item is one grave match:

| Field | Description |
| --- | --- |
| `fullName` | Surname and given name |
| `cemetery` | Cemetery name |
| `section` | Section (`Část`) |
| `department` | Department (`Oddělení`) |
| `graveNumber` | Grave number |
| `cemeteryOffice` | Cemetery office (`HS`) |
| `searchSurname` / `searchFirstName` / `searchBirthYear` / `searchDeathYear` | Echo of the query |

### How it works

1. Loads the search form and session cookie
2. Reads the security code from the HTML and posts the search
3. Parses the results table into the dataset

### Local run

```bash
apify run
```

Put input in `storage/key_value_stores/default/INPUT.json`. Results land in `storage/datasets/default/`.

### Limitations

- Surname is required by the cemetery site
- Only years are supported for birth/death, not full dates
- Result rows do not include birth or death dates
- Very broad queries may be rejected as “too many records”

### Resources

- [Apify SDK for JavaScript](https://docs.apify.com/sdk/js)
- [Crawlee](https://crawlee.dev/)
- [Actor development](https://docs.apify.com/platform/actors/development)

# Actor input Schema

## `surname` (type: `string`):

Surname of the deceased (required by the cemetery search). Accent-insensitive.

## `firstName` (type: `string`):

Optional first name of the deceased.

## `birthYear` (type: `integer`):

Optional birth year (4 digits). The site does not support full dates.

## `deathYear` (type: `integer`):

Optional death or burial year (4 digits). The site does not support full dates.

## `cemetery` (type: `string`):

Optional cemetery filter. Leave as All cemeteries to search everywhere.

## Actor input object example

```json
{
  "surname": "Masaryk",
  "cemetery": "0"
}
```

# 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 = {
    "surname": "Masaryk"
};

// Run the Actor and wait for it to finish
const run = await client.actor("calvera/prague-graves").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 = { "surname": "Masaryk" }

# Run the Actor and wait for it to finish
run = client.actor("calvera/prague-graves").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 '{
  "surname": "Masaryk"
}' |
apify call calvera/prague-graves --silent --output-dataset

```

## MCP server setup

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

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/dZSolJ7n6P1ckNCfg/builds/ag4RkArAmQG8ZVWQG/openapi.json