# Indeed MCP Server (`axlymxp/indeed-mcp-server`) Actor

MCP server + scraper for Indeed jobs. Let Claude, ChatGPT, Cursor and n8n search jobs, fetch full listings and autocomplete locations live via Model Context Protocol — or run it as a classic Indeed scraper. Pay per tool call.

- **URL**: https://apify.com/axlymxp/indeed-mcp-server.md
- **Developed by:** [axly](https://apify.com/axlymxp) (community)
- **Categories:** Jobs, AI
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## Indeed MCP Server

**Give your AI agent live access to Indeed.** This Actor is a [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server that lets Claude, ChatGPT, Cursor, n8n, and any other MCP-compatible client **search Indeed jobs, pull full job listings, and autocomplete locations and companies in real time** — no scraping code required.

Prefer a classic scraper? The same Actor also runs as a one-shot dataset scraper when you give it a search query.

***

### What it does

Expose Indeed to your AI agent as four tools:

| Tool | What it returns |
| --- | --- |
| `search_indeed_jobs` | Job listings for a keyword + location: title, company, salary range, rating, location, snippet, apply link |
| `get_indeed_job` | Full detail for one job: complete description, precise salary, employment type, address, direct-apply flag |
| `suggest_indeed_locations` | Location autocomplete suggestions (e.g. "New York, NY") |
| `suggest_indeed_companies` | Company / keyword autocomplete suggestions |

Works across **25 Indeed country sites** (US, UK, Canada, Australia, India, Germany, France, and more).

***

### Use cases

- **AI job-search assistants** — let an agent find and compare live openings for a user.
- **Recruiting research** — pull candidate-facing listings, salaries and company signals on demand.
- **Salary benchmarking** — ask your agent to gather salary ranges for a role across cities.
- **Workflow automation (n8n / Make)** — trigger Indeed lookups inside no-code automations.
- **Classic scraping** — run it without MCP to dump a job dataset for a query.

***

### Connect it to your AI agent

1. Start this Actor in **Standby mode** (it runs as a persistent server).

2. Point your MCP client at the Standby URL with the `/mcp` path:

   ```
   https://<your-actor-standby-url>/mcp
   ```

3. Add your Apify API token as a header:

   ```
   Authorization: Bearer <APIFY_API_TOKEN>
   ```

#### Claude Desktop example

```json
{
  "mcpServers": {
    "indeed": {
      "url": "https://<your-actor-standby-url>/mcp",
      "headers": { "Authorization": "Bearer <APIFY_API_TOKEN>" }
    }
  }
}
```

Then just ask: *"Find remote senior Python jobs on Indeed and list their salaries and apply links."*

***

### Example tool call

`search_indeed_jobs`:

```json
{
  "query": "software engineer",
  "location": "Remote",
  "country": "us",
  "limit": 20,
  "sort": "date"
}
```

Returns:

```json
{
  "query": "software engineer",
  "country": "us",
  "count": 20,
  "results": [
    {
      "jobkey": "abc123",
      "title": "Senior Software Engineer",
      "company": "Acme Corp",
      "location_city": "Remote",
      "salary_min": 140000,
      "salary_max": 180000,
      "salary_currency": "USD",
      "salary_period": "YEARLY",
      "job_types": ["Full-time"],
      "company_rating": 4.1,
      "snippet": "We are hiring a senior engineer to ...",
      "url": "https://www.indeed.com/viewjob?jk=abc123"
    }
  ]
}
```

***

### Classic scraper mode

Run the Actor normally (not Standby) with an input like:

```json
{
  "query": "data analyst",
  "location": "London",
  "country": "uk",
  "limit": 100,
  "fetchDetails": true
}
```

It searches Indeed and pushes normalized job rows to the dataset.

***

### Output fields

Each job includes: `jobkey`, `title`, `company`, `company_rating`, `location_city`, `location_state`, `location_postal`, `salary_min`, `salary_max`, `salary_currency`, `salary_period`, `job_types`, `snippet`, `description`, `is_remote`, `apply_url`, `url`, `pub_date`, `create_date`, `scraped_at`, and more.

***

### Reliability & proxies

Indeed is protected by Cloudflare. For dependable results, run with **Apify Residential proxies** (the default). Anonymous access is best for the first result page per query — broaden coverage by varying the query, location and filters rather than deep pagination.

***

### Notes

- This Actor returns publicly visible job-listing data. Respect Indeed's Terms of Service and applicable law; use the data responsibly.
- Not affiliated with or endorsed by Indeed.

### FAQ

**Do I need to write code?** No. In MCP mode your AI agent calls the tools directly.

**Which countries are supported?** 25 Indeed country sites, selectable per call/run.

**Can it get full descriptions and exact salaries?** Yes — use `get_indeed_job` (MCP) or `fetchDetails: true` (classic mode).

**Can I use it without MCP?** Yes — run it as a normal scraper with a `query`.

# Actor input Schema

## `query` (type: `string`):

Job title or keywords to search on Indeed. Required only for classic (non-MCP) scraping runs.

## `location` (type: `string`):

City, state, ZIP or 'Remote'. Leave empty for nationwide results.

## `country` (type: `string`):

Indeed country site to search.

## `limit` (type: `integer`):

Maximum number of jobs to retrieve in a classic run.

## `fetchDetails` (type: `boolean`):

Enrich each job with the full description, precise salary and address (slower, more requests).

## `jobType` (type: `string`):

Filter by employment type.

## `maxAgeDays` (type: `integer`):

Only include jobs posted within this many days.

## `sort` (type: `string`):

How to sort results.

## `proxyConfiguration` (type: `object`):

Indeed is protected by Cloudflare — Apify Residential proxies are strongly recommended for reliable results.

## Actor input object example

```json
{
  "query": "software engineer",
  "location": "New York, NY",
  "country": "us",
  "limit": 50,
  "fetchDetails": false,
  "jobType": "",
  "sort": "relevance",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# 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 = {
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("axlymxp/indeed-mcp-server").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 = { "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    } }

# Run the Actor and wait for it to finish
run = client.actor("axlymxp/indeed-mcp-server").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 '{
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call axlymxp/indeed-mcp-server --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/9ECm4K8FiipSE0XEu/builds/5cJPdg2IJ49aA10zf/openapi.json