# Practo Doctor Scraper (`fervent_bus/practo-doctor-scraper`) Actor Get verified doctor profiles, consultation fees, ratings and clinic addresses from Practo.com — India's largest health platform. Covers 20+ cities and 50+ specialties. Structured JSON, ready for Claude, ChatGPT and any AI agent. - **URL**: https://apify.com/fervent\_bus/practo-doctor-scraper.md - **Developed by:** [Archit Khurana](https://apify.com/fervent_bus) (community) - **Categories:** AI, Lead generation, Automation - **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 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/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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## India Doctor & Clinic Scraper — Fees, Ratings & Verified Profiles The only structured data source you need for Indian doctors. Ask Claude or ChatGPT *"find me the top-rated cardiologists in Mumbai with consultation fees under ₹800"* — this is the actor that makes that question answerable. Pulls live data from **Practo.com**, India's largest healthcare platform with 100,000+ verified doctor profiles across every major city and specialty. Returns clean JSON ready for AI pipelines, CRMs, spreadsheets or dashboards. --- ### What you get Every doctor record includes: | Field | Example | |---|---| | `doctorName` | Dr. Priya Sharma | | `specialty` | Dermatologist | | `experienceYears` | 14 | | `qualifications` | MBBS, MD - Dermatology | | `consultationFee` | 800 *(INR)* | | `clinicName` | Skin & Smile Clinic | | `clinicAddress` | 42, MG Road, Indiranagar, Bangalore | | `locality` | Indiranagar | | `city` | Bangalore | | `reviewCount` | 312 | | `isVerified` | true | | `onlineConsultationAvailable` | true | | `profileUrl` | https://www.practo.com/bangalore/doctor/... | --- ### Why this beats every alternative **vs Google Maps** — Maps shows clinics, not doctors. No fees, no qualifications, no specialty-level search. This actor returns the actual doctor behind the clinic with their credentials and pricing. **vs manual research** — Practo has 100,000+ profiles. Manually collecting 50 doctors with fees, ratings and addresses would take days. This does it in minutes. **vs other scrapers** — Built specifically for Practo's React/Redux architecture. Extracts data from the server-rendered state blob, not brittle HTML selectors that break every week. --- ### Example input ```json { "city": "Bangalore", "specialty": "dermatologist", "maxResults": 100, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` **Works for any combination of:** Cities — Delhi, Mumbai, Bangalore, Hyderabad, Chennai, Pune, Kolkata, Ahmedabad, Jaipur, Chandigarh, Kochi, Lucknow, Nagpur, Indore, Surat, Visakhapatnam, Coimbatore and 10+ more. Specialties — `dentist`, `cardiologist`, `dermatologist`, `gynecologist`, `orthopedic-surgeon`, `pediatrician`, `general-physician`, `psychiatrist`, `neurologist`, `gastroenterologist`, `ophthalmologist`, `ent-specialist`, `urologist`, `oncologist`, `endocrinologist` and 35+ more. *** ### Example output ```json [ { "doctorName": "Dr. Sourabh Nagpal", "specialty": "Dentist", "experienceYears": 21, "qualifications": "BDS, MDS - Prosthodontist And Crown Bridge", "consultationFee": 500, "clinicName": "Matrix Dental & Skin Lounge", "clinicAddress": "14, Ground Floor, Poorvi Marg, Vasant Vihar, Delhi", "locality": "Vasant Vihar", "city": "Delhi", "rating": null, "reviewCount": 1701, "isVerified": true, "onlineConsultationAvailable": true, "profileUrl": "https://www.practo.com/delhi/doctor/dr-sourabh-nagpal-dentist", "phone": null } ] ``` *** ### Use with AI agents #### Ask Claude (via Anthropic API) ```python import anthropic import apify_client ## 1. Scrape the data client = apify_client.ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("fervent_bus/india-doctor-scraper").call(run_input={ "city": "Mumbai", "specialty": "cardiologist", "maxResults": 50 }) doctors = list(client.dataset(run["defaultDatasetId"]).iterate_items()) ## 2. Ask Claude anything about it anthropic_client = anthropic.Anthropic() message = anthropic_client.messages.create( model="claude-sonnet-5", max_tokens=1024, messages=[{ "role": "user", "content": f"Which 5 cardiologists in Mumbai have the best reviews and offer online consultation? Data: {doctors}" }] ) print(message.content[0].text) ``` #### Ask ChatGPT ```python import openai, json openai_client = openai.OpenAI() response = openai_client.chat.completions.create( model="gpt-4o", messages=[{ "role": "user", "content": f"Summarise the dermatologist market in Bangalore — average fees, top-rated doctors, most common qualifications. Data: {json.dumps(doctors)}" }] ) print(response.choices[0].message.content) ``` #### MCP tool definition (for any agent framework) ```json { "name": "find_doctors_india", "description": "Find doctors and clinics in any Indian city by specialty. Returns fees, ratings, qualifications and addresses.", "parameters": { "city": { "type": "string", "description": "Indian city e.g. Delhi, Mumbai, Bangalore" }, "specialty": { "type": "string", "description": "Medical specialty e.g. cardiologist, dentist, dermatologist" }, "maxResults": { "type": "integer", "default": 20 } } } ``` *** ### Real use cases **Healthcare sales & lead gen** — Pharma reps, medical device companies and health-tech startups use this to build targeted lists of specialist doctors with clinic addresses for outreach. **Insurance network mapping** — Build and verify provider directories. Cross-check which doctors and clinics are active in a city before adding them to a network. **Market research** — Compare consultation fee ranges, doctor density and review volumes across cities. Essential for any healthtech product deciding where to launch. **Clinic aggregator / booking platform** — Seed your own platform with real clinic and doctor data rather than building a directory from scratch. **AI health assistants** — Let users ask natural-language questions like *"Who is the best gynecologist in South Delhi with online consult under ₹500?"* and power the answer with real data. **Academic research** — Study healthcare access, fee distribution and specialist availability across Indian cities and tiers. *** ### Pricing **$0.004 per result** — 1,000 doctor records for $4. *** ### Notes - Requires **Apify Residential Proxies** — enable in the `proxyConfiguration` input (pre-filled). Practo blocks datacenter IPs. - Specialty must match Practo's URL slugs: lowercase, hyphenated e.g. `general-physician`, `orthopedic-surgeon`. - `phone` and `rating` are `null` in listing results — Practo doesn't expose phone numbers publicly and star ratings only appear on individual profile pages. - Adds a 2–4s random delay between pages. *** Built with [Apify](https://apify.com) · [Camoufox](https://github.com/daijro/camoufox) · Source on [GitHub](https://github.com/roshtarg-cpu/practo-doctor-scraper) # Actor input Schema ## `city` (type: `string`): Indian city to search in e.g. Delhi, Mumbai, Bangalore ## `specialty` (type: `string`): Doctor specialty slug e.g. dentist, cardiologist, dermatologist, general-physician ## `maxResults` (type: `integer`): Maximum number of doctors to scrape ## `proxyConfiguration` (type: `object`): Use Apify residential proxies to avoid blocks. ## Actor input object example ```json { "city": "Delhi", "specialty": "dentist", "maxResults": 10, "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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "city": "Delhi", "specialty": "dentist", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("fervent_bus/practo-doctor-scraper").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 = { "city": "Delhi", "specialty": "dentist", "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("fervent_bus/practo-doctor-scraper").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 '{ "city": "Delhi", "specialty": "dentist", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call fervent_bus/practo-doctor-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fervent_bus/practo-doctor-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Practo Doctor Scraper", "description": "Get verified doctor profiles, consultation fees, ratings and clinic addresses from Practo.com — India's largest health platform. Covers 20+ cities and 50+ specialties. Structured JSON, ready for Claude, ChatGPT and any AI agent.", "version": "0.0", "x-build-id": "Mvew9QXurdqw5oAQD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fervent_bus~practo-doctor-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fervent_bus-practo-doctor-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fervent_bus~practo-doctor-scraper/runs": { "post": { "operationId": "runs-sync-fervent_bus-practo-doctor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fervent_bus~practo-doctor-scraper/run-sync": { "post": { "operationId": "run-sync-fervent_bus-practo-doctor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "city", "specialty" ], "properties": { "city": { "title": "City", "type": "string", "description": "Indian city to search in e.g. Delhi, Mumbai, Bangalore" }, "specialty": { "title": "Specialty", "type": "string", "description": "Doctor specialty slug e.g. dentist, cardiologist, dermatologist, general-physician" }, "maxResults": { "title": "Max Results", "type": "integer", "description": "Maximum number of doctors to scrape", "default": 10 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Use Apify residential proxies to avoid blocks." } } }, "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 } } } } } } } } } } ```