# megAgence Consultants · Full profiles infos (emails, phones) (`corent1robert/megagence-consultants`) Actor For teams needing the megAgence France directory: names, phones, cities, geo, badges, profile links. Export full list or filter by name—JSON for CRM. Email not published on megagence.com. Custom work: corentin@outreacher.fr - **URL**: https://apify.com/corent1robert/megagence-consultants.md - **Developed by:** [Corentin Robert](https://apify.com/corent1robert) (community) - **Categories:** Lead generation, Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.99 / 1,000 results 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 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 ## megAgence — independent consultant directory (France) **Who it’s for:** teams that need an **export-ready list** of megAgence independent consultants with **phone numbers**, **cities**, **coverage areas**, **map coordinates**, **badges**, and **links to public profile pages** on megagence.com. **What you get:** one row per consultant from the **same public directory** visitors use on the website. **Professional email is not included** — megagence.com does not show consultant emails in its public finder or on profile pages; you get phone and profile URLs for outreach workflows that respect that design. **Trust:** data reflects the published directory; use it in line with megAgence terms and applicable law. --- ### What you get | Field | Description | |--------|-------------| | `consultantId` | Consultant id used on megagence.com | | `firstName` / `lastName` | Name | | `city` / `postCode` | Location | | `phone` | Phone as shown on the directory | | `mainArea` | Primary coverage label | | `lat` / `lng` | Coordinates when provided | | `badges` | Program badges (e.g. senior, excellence) | | `profileUrl` | Public `votre-consultant` page | | `photoUrl` | Thumbnail photo URL | ### Important - **No professional email field.** The public search and profile pages do not expose consultant email addresses; this Actor cannot add them. Phone and profile URL are the primary contact paths from public data. - Results come from the **same public data** the on-site search uses. Comply with megAgence terms and privacy / marketing rules. - **Empty name filter** = full list the directory returns for a blank search. **Partial name** = same narrowing as typing in the website search box. ### Quick start (Apify Console) 1. Open the Actor. Leave **Name filter** empty for the full list, or type part of a name to narrow. 2. Start the run. 3. Open the **Dataset** for JSON or Excel; open **Run log** in the key-value store for live progress. ### Input | Field | Default | Description | |--------|---------|-------------| | `searchQuery` | `""` | Empty = full list; otherwise partial name (same idea as the website search) | | `maxResults` | `0` | Cap rows (`0` = all rows returned) | | `concurrency` | `55` | How many rows are written to the dataset at once | | `fetchTimeout` | `60000` | Max wait for the directory response (milliseconds) | ```json { "searchQuery": "" } ```` ### How it works 1. Calls the **public megAgence consultant search** (same origin as the website finder). 2. Normalizes each consultant into one dataset row (names, phone, location, geo, badges, links). 3. Saves every row to your Apify dataset. 4. Writes a **RUN\_LOG** text file so you can follow long runs. ### Output - **Dataset:** one JSON object per consultant. - **RUN\_LOG:** live text log in the default key-value store. #### Sample record ```json { "consultantId": "579", "lastName": "ABITBOL-MORRONI", "firstName": "Patricia", "postCode": "94170", "city": "LE PERREUX SUR MARNE", "phone": "06 40 07 16 16", "mainArea": "Le Perreux-sur-Marne (94170)", "lat": 48.8435, "lng": 2.50418, "badges": ["major-consultant", "senior-consultant", "expert-consultant", "club-excellence"], "profileUrl": "https://www.megagence.com/votre-consultant/patricia-abitbol-morroni/579", "photoUrl": "https://www.megagence.com/photos_agences/petit/nego_72001553.jpg" } ``` ### Local development ```bash npm install echo '{"searchQuery":"","maxResults":30}' > input.json apify run ``` After a successful run, `output.csv` is written next to `input.json` (semicolon-separated, UTF-8 BOM for Excel). ### Support Contact if you need a custom scraper or tailored automation. ### Internals - **HTTP** request to the public JSON search URL (`Accept: application/json`). No headless browser. - Apify Proxy is enabled by default in the cloud when available. # Actor input Schema ## `searchQuery` (type: `string`): Leave blank for everyone in the directory snapshot. Otherwise enter part of a first or last name. ## `maxResults` (type: `integer`): 0 = full result. Use a small number for a quick test run. ## `concurrency` (type: `integer`): Higher values can speed up saving when you export many rows. ## `fetchTimeout` (type: `integer`): Maximum time to wait for the directory to respond. ## Actor input object example ```json { "searchQuery": "", "maxResults": 20, "concurrency": 55, "fetchTimeout": 60000 } ``` # Actor output Schema ## `dataset` (type: `string`): All consultants as JSON — open the Dataset tab or export CSV / Excel. ## `overview` (type: `string`): Slim columns for CRM: name, city, phone, profile URL. ## `runLog` (type: `string`): Progress while saving rows. # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxResults": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("corent1robert/megagence-consultants").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "maxResults": 20 } # Run the Actor and wait for it to finish run = client.actor("corent1robert/megagence-consultants").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 '{ "maxResults": 20 }' | apify call corent1robert/megagence-consultants --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=corent1robert/megagence-consultants", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "megAgence Consultants · Full profiles infos (emails, phones)", "description": "For teams needing the megAgence France directory: names, phones, cities, geo, badges, profile links. Export full list or filter by name—JSON for CRM. Email not published on megagence.com. Custom work: corentin@outreacher.fr", "version": "1.1", "x-build-id": "5eneGjVKZcfKb0U4c" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/corent1robert~megagence-consultants/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-corent1robert-megagence-consultants", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/corent1robert~megagence-consultants/runs": { "post": { "operationId": "runs-sync-corent1robert-megagence-consultants", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/corent1robert~megagence-consultants/run-sync": { "post": { "operationId": "run-sync-corent1robert-megagence-consultants", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQuery": { "title": "Name filter (optional)", "type": "string", "description": "Leave blank for everyone in the directory snapshot. Otherwise enter part of a first or last name.", "default": "" }, "maxResults": { "title": "Max rows", "minimum": 0, "type": "integer", "description": "0 = full result. Use a small number for a quick test run.", "default": 0 }, "concurrency": { "title": "Save parallelism", "minimum": 3, "maximum": 100, "type": "integer", "description": "Higher values can speed up saving when you export many rows.", "default": 55 }, "fetchTimeout": { "title": "Request timeout (ms)", "minimum": 15000, "type": "integer", "description": "Maximum time to wait for the directory to respond.", "default": 60000 } } }, "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 } } } } } } } } } } ```