# Glassdoor Salary & Reviews Intel - MCP Server (`seibs.co/mcp-glassdoor-salary-intel`) Actor

MCP tool server giving AI agents logged-out Glassdoor comp benchmarks, rating sub-scores, review themes, and interview intel as structured tools; x402/Skyfire-ready. Five tools: get\_company\_overview, get\_salary\_benchmarks, get\_review\_intel, get\_interview\_intel, compare\_companies.

- **URL**: https://apify.com/seibs.co/mcp-glassdoor-salary-intel.md
- **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community)
- **Categories:** MCP servers, Jobs, Business
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$5.00 / 1,000 mcp tool calls

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

## Glassdoor Salary & Reviews Intel - MCP Server

> Model Context Protocol (MCP) server wrapper for [glassdoor-salary-intel](https://apify.com/seibs.co/glassdoor-salary-intel). Gives AI agents direct, pay-per-call access to logged-out Glassdoor comp benchmarks, rating sub-scores, review themes, and interview intel - no API token required when called over x402 / Skyfire.

### What it is

A thin MCP server that exposes the Glassdoor intel engine as five typed tools an AI agent can call. Each tool runs the upstream `glassdoor-salary-intel` actor against logged-out public Glassdoor pages and reshapes the result into small, deterministic JSON (no full review bodies, no named reviewers). Built for comp-analysis copilots, recruiting agents, candidate-prep bots, and employer-research workflows.

Honest note: each tool call triggers a live upstream run. Glassdoor sits behind Cloudflare and is fetched through a residential proxy, so a single call can take up to a minute under adverse conditions, and an occasional company will come back blocked or unresolved (the tool returns `ok=false` with a reason rather than crashing).

### Tools

| Tool | Args | Returns |
|---|---|---|
| `get_company_overview` | `company` | One slim company record: overall rating, every rating sub-score, recommend-to-friend %, CEO approval %, firmographics. |
| `get_salary_benchmarks` | `company`, `role_filter?` (list), `max_datapoints?` (<=100) | Per-role salary datapoint rows (base min/p25/median/p75/max, total comp, currency, sample count) + a one-line median summary. |
| `get_review_intel` | `company`, `max_reviews_sampled?` (<=300) | One aggregated review-intelligence record: rating histogram, rating trend by year, top pros/cons/advice keyword themes, anonymized excerpts. |
| `get_interview_intel` | `company` | Interview difficulty score/label, candidate experience split, offer rate, interview count, common questions. |
| `compare_companies` | `companies` (list, 2-5) | Slim company records sorted by overall rating, with a one-line comparison summary. |

### Run modes

- `list_tools` - emit the tool catalog (free, no charge) including the agentic-payment descriptor.
- `call_tool` - invoke one tool. Requires `tool` + `args`.
- `batch` - invoke up to 10 `{tool, args}` calls in one run.

```json
{
  "mode": "call_tool",
  "tool": "get_salary_benchmarks",
  "args": { "company": "Stripe", "role_filter": ["software engineer"], "max_datapoints": 25 }
}
````

### How agents call it

This is a standard Apify actor-as-tool MCP server. Point your MCP host (Claude, OpenAI Responses, LangChain, LlamaIndex) at the Apify MCP endpoint and it will discover the five tools from the `list_tools` catalog, then call them with `call_tool`.

This server is also **x402 (USDC on Base)** and **Skyfire** ready. When the operator enables Apify MCP monetization, an AI agent can pay per tool call with no pre-provisioned API token. The `list_tools` response includes a `payments` descriptor advertising the accepted rails and per-call price. Operators enable rails via environment variables:

| Env | Purpose |
|---|---|
| `X402_ENABLED` | `1` to advertise x402 acceptance |
| `X402_PAY_TO_ADDRESS` | receiving wallet (USDC on Base) |
| `X402_PRICE_USD` | per-call price advertised (default 0.005) |
| `SKYFIRE_ENABLED` | `1` to advertise Skyfire acceptance |
| `SKYFIRE_SELLER_ID` | Skyfire seller identity |

Calls through Apify always bill via standard PPE (`mcp_tool_call` $0.005 + upstream pass-through); x402/Skyfire are the token-less rails layered on top for direct agents.

### Pricing

Flat **$0.005 per MCP tool call**, plus the upstream `glassdoor-salary-intel` PPE pass-through billed to the same run (`company_record` $0.010, `salary_datapoint` $0.004, `review_enrichment` $0.008, `interview_intel` $0.010). A run that returns nothing costs nothing on the upstream side.

### Responsible use / data scope

The upstream actor reads only logged-out, public Glassdoor pages (Overview / Salary / Reviews / Interview) - no accounts, no cookies, no ToS acceptance, no login walls. PII is minimized hard: the tools surface salary aggregates, rating sub-scores, and keyword-frequency review *themes* (plus optional name-stripped short excerpts), never named reviewers, usernames, or full individual review bodies. You are responsible for lawful use of the outputs. See the upstream actor's README for the full data-scope note.

### Related Actors

- [glassdoor-salary-intel](https://apify.com/seibs.co/glassdoor-salary-intel) - the non-MCP actor with full input controls, monitor mode, and CSV/HTML artifacts.
- [mcp-hiring-signal-intel](https://apify.com/seibs.co/mcp-hiring-signal-intel) - MCP twin for live job-postings and hiring-surge intel.

### Support

Issues or coverage gaps: open an issue on the actor page, or leave a quick review: https://apify.com/seibs.co/mcp-glassdoor-salary-intel#reviews

# Actor input Schema

## `mode` (type: `string`):

list\_tools = emit the MCP tool catalog (free). call\_tool = invoke one tool (requires 'tool' + 'args'). batch = invoke a list of {tool, args} calls (max 10 per run).

## `tool` (type: `string`):

Required when mode=call\_tool. One of: get\_company\_overview, get\_salary\_benchmarks, get\_review\_intel, get\_interview\_intel, compare\_companies.

## `args` (type: `object`):

Arguments for the selected tool. Example for get\_salary\_benchmarks: {"company": "Stripe", "role\_filter": \["software engineer"], "max\_datapoints": 25}. Example for compare\_companies: {"companies": \["Stripe", "Databricks"]}.

## `calls` (type: `array`):

Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: \[{"tool": "get\_company\_overview", "args": {"company": "Stripe"}}, {"tool": "get\_salary\_benchmarks", "args": {"company": "Stripe", "role\_filter": \["engineer"]}}]. Max 10 calls per run.

## Actor input object example

```json
{
  "mode": "list_tools",
  "tool": "get_company_overview",
  "args": {
    "company": "Stripe"
  },
  "calls": []
}
```

# 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 = {
    "mode": "list_tools",
    "args": {
        "company": "Stripe"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("seibs.co/mcp-glassdoor-salary-intel").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 = {
    "mode": "list_tools",
    "args": { "company": "Stripe" },
}

# Run the Actor and wait for it to finish
run = client.actor("seibs.co/mcp-glassdoor-salary-intel").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 '{
  "mode": "list_tools",
  "args": {
    "company": "Stripe"
  }
}' |
apify call seibs.co/mcp-glassdoor-salary-intel --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=seibs.co/mcp-glassdoor-salary-intel",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Glassdoor Salary & Reviews Intel - MCP Server",
        "description": "MCP tool server giving AI agents logged-out Glassdoor comp benchmarks, rating sub-scores, review themes, and interview intel as structured tools; x402/Skyfire-ready. Five tools: get_company_overview, get_salary_benchmarks, get_review_intel, get_interview_intel, compare_companies.",
        "version": "0.1",
        "x-build-id": "QDDsDam33uoafgYMf"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/seibs.co~mcp-glassdoor-salary-intel/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-seibs.co-mcp-glassdoor-salary-intel",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/seibs.co~mcp-glassdoor-salary-intel/runs": {
            "post": {
                "operationId": "runs-sync-seibs.co-mcp-glassdoor-salary-intel",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/seibs.co~mcp-glassdoor-salary-intel/run-sync": {
            "post": {
                "operationId": "run-sync-seibs.co-mcp-glassdoor-salary-intel",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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",
                "required": [
                    "mode"
                ],
                "properties": {
                    "mode": {
                        "title": "Mode",
                        "enum": [
                            "list_tools",
                            "call_tool",
                            "batch"
                        ],
                        "type": "string",
                        "description": "list_tools = emit the MCP tool catalog (free). call_tool = invoke one tool (requires 'tool' + 'args'). batch = invoke a list of {tool, args} calls (max 10 per run).",
                        "default": "list_tools"
                    },
                    "tool": {
                        "title": "Tool name",
                        "enum": [
                            "get_company_overview",
                            "get_salary_benchmarks",
                            "get_review_intel",
                            "get_interview_intel",
                            "compare_companies"
                        ],
                        "type": "string",
                        "description": "Required when mode=call_tool. One of: get_company_overview, get_salary_benchmarks, get_review_intel, get_interview_intel, compare_companies.",
                        "default": "get_company_overview"
                    },
                    "args": {
                        "title": "Tool arguments (JSON object)",
                        "type": "object",
                        "description": "Arguments for the selected tool. Example for get_salary_benchmarks: {\"company\": \"Stripe\", \"role_filter\": [\"software engineer\"], \"max_datapoints\": 25}. Example for compare_companies: {\"companies\": [\"Stripe\", \"Databricks\"]}."
                    },
                    "calls": {
                        "title": "Batch calls",
                        "maxItems": 10,
                        "type": "array",
                        "description": "Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: [{\"tool\": \"get_company_overview\", \"args\": {\"company\": \"Stripe\"}}, {\"tool\": \"get_salary_benchmarks\", \"args\": {\"company\": \"Stripe\", \"role_filter\": [\"engineer\"]}}]. Max 10 calls per run.",
                        "default": []
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```