# CFP Financial Planner Directory Scraper (`jungle_synthesizer/cfp-financial-planner-directory-scraper`) Actor Scrapes fee-only CERTIFIED FINANCIAL PLANNER® professionals from the NAPFA (National Association of Personal Financial Advisors) public directory. Returns advisor contact info, firm details, credentials, specialties, compensation model, and years of experience. - **URL**: https://apify.com/jungle\_synthesizer/cfp-financial-planner-directory-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## NAPFA Fee-Only Financial Advisor Directory Scraper Scrapes advisor and firm profiles from the [NAPFA (National Association of Personal Financial Advisors) public directory](https://www.napfa.org/find-an-advisor). Returns name, contact info, credentials, compensation model, specialties, and years of experience for fee-only certified financial planners across the United States — roughly 4,000 NAPFA-registered advisors in total. --- ### NAPFA Advisor Scraper Features - Extracts advisor and firm data from the NAPFA public directory — no login, no API key, no cost per record beyond standard pricing - Returns 20+ fields per advisor including compensation model (fee-only, AUM, hourly), specialties, and NAPFA membership year - Covers all 50 US states by searching ~70 major cities by default — the full NAPFA advisor population in a single run - Deduplicates across overlapping city queries by `memberId` so each advisor appears exactly once - Supports custom city lists if you only need specific regions - No proxies needed. NAPFA's search returns clean JSON embedded in the page response --- ### Who Uses NAPFA Advisor Data? - **Fintech and wealth-tech startups** — build advisor search tools, CRM imports, or network analysis on the fee-only segment - **Custodian and RIA platform sales teams** — identify and target independent fee-only advisors for platform outreach - **Practice management software vendors** — enrich prospect lists with NAPFA credentials and specialties - **Compliance and regulatory researchers** — cross-reference NAPFA membership against FINRA BrokerCheck or SEC Form ADV data - **Marketing agencies serving RIAs** — segment advisors by specialty (ESG, divorce, small-business) for targeted campaigns - **Financial data aggregators** — complement FINRA and SEC Form ADV datasets with the fee-only certified-planner segment --- ### How NAPFA Advisor Scraper Works 1. Build search URLs for a list of US cities — either the default set of ~70 cities covering all 50 states, or a custom list you provide 2. For each city, fetch the NAPFA search page and extract the `window.faaResults` JSON embedded in the HTML response — no XHR, no browser required 3. Iterate through firms and members in the results, merge firm-level address and website data into each advisor record, and deduplicate by `memberId` 4. Save one flat record per advisor and stop when `maxItems` is reached --- ### Input ```json { "maxItems": 100, "cities": ["New York", "Chicago", "Denver", "Seattle"] } ```` | Field | Type | Default | Description | |-------|------|---------|-------------| | `maxItems` | integer | `10` | Maximum number of advisor records to return | | `cities` | array of strings | ~70 US cities | City names or zip codes to search. Defaults to a curated set covering all 50 states | Leave `cities` empty to scrape the full NAPFA directory with the default city list. Supply a custom list when you only need specific regions. *** ### NAPFA Advisor Scraper Output Fields ```json { "advisor_name": "Arthur Flores", "first_name": "Arthur", "last_name": "Flores", "credentials": "CFP®", "firm_name": "Flores Wealth Planning, LLC", "city": "New York", "state": "NY", "zip": "10005", "address": "48 Wall Street, Suite 1100", "phone": "(917) 740-3898", "email": "aflores@floresplanning.com", "website": "https://floresfinancialplanning.com", "compensation_model": "Hourly", "specialties": "High Net Worth Client Needs; Retirement Planning & Distribution Rules; Tax Planning", "years_experience": 30, "napfa_member_since": 2012, "member_id": 27996, "firm_id": 38287, "source": "NAPFA", "profile_url": "https://www.napfa.org/find-an-advisor?q=New+York", "scraped_at": "2026-05-06T10:46:26.322Z" } ``` | Field | Type | Description | |-------|------|-------------| | `advisor_name` | string | Full name (First Last) | | `first_name` | string | Advisor first name | | `last_name` | string | Advisor last name | | `credentials` | string | Comma-separated designations (e.g. `CFP®`) | | `firm_name` | string | Advisory firm name | | `city` | string | City where the firm is located | | `state` | string | State abbreviation | | `zip` | string | Postal code | | `address` | string | Street address | | `phone` | string | Work phone number | | `email` | string | Advisor contact email | | `website` | string | Firm website URL | | `compensation_model` | string | Fee structure (e.g. `Fee-Only`, `AUM`, `Hourly`, `Fixed Fee`) | | `specialties` | string | Semicolon-separated planning specialties and client markets served | | `years_experience` | integer | Years of industry experience (calculated from NAPFA's `industryStartDate`) | | `napfa_member_since` | integer | Year the advisor joined NAPFA | | `member_id` | integer | NAPFA member ID — stable cross-reference key | | `firm_id` | integer | NAPFA firm ID | | `source` | string | Always `"NAPFA"` | | `profile_url` | string | Search URL that returned this record | | `scraped_at` | string | ISO 8601 timestamp | *** ### 🔍 FAQ #### How do I scrape NAPFA financial advisor data? NAPFA Advisor Scraper handles it. Configure `maxItems` and optionally supply a `cities` list, then run it. The scraper fetches search result pages, parses the embedded JSON, and returns one record per advisor. No proxies, no browser. #### How much does NAPFA Advisor Scraper cost to run? NAPFA Advisor Scraper charges $0.10 per start plus $0.001 per advisor record. A full directory run returning 4,000 advisors costs roughly $4.10. A small regional pull of 200 advisors costs about $0.30. #### Does NAPFA Advisor Scraper need proxies? It does not. NAPFA's find-an-advisor page serves clean HTML without rate limiting or anti-bot measures at normal concurrency levels. #### What data does NAPFA contain that I can't get from FINRA BrokerCheck or SEC Form ADV? NAPFA membership is a distinct credential — it specifically identifies advisors who have committed to the fee-only compensation model and meet NAPFA's fiduciary standard. BrokerCheck and Form ADV cover regulatory registrations broadly. NAPFA data adds the compensation model filter and specialty breakdown that regulatory filings don't surface cleanly. #### Can I filter by specialty or compensation model? The scraper returns all advisors from the city searches you specify, then you filter the output dataset by `compensation_model` or `specialties` fields using Apify's dataset filter tools or your own pipeline. *** ### Need More Features? Need custom field extraction, state-level filtering, or integration with FINRA BrokerCheck or SEC Form ADV data? [File an issue](https://console.apify.com/actors/aTAKS3h16EmsTLnMu/issues) or get in touch. ### Why Use NAPFA Advisor Scraper? - **Affordable** — $0.001 per record. The full ~4,000-advisor NAPFA directory costs under $5 - **Fee-only segment** — NAPFA membership specifically identifies advisors who have committed to the fee-only model, which is exactly what Altruist, Savvy Wealth, and similar fintech platforms care about — not the broader broker-dealer population - **Clean output** — returns structured JSON with consistent field names, so you spend less time normalizing and more time using it # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of advisors to return. Default is 10 for quick test runs. ## `cities` (type: `array`): List of US city names or zip codes to search. Each city search returns all NAPFA advisors near that location. Defaults to a curated list of ~60 major US cities covering all 50 states. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "cities": [ "New York", "Los Angeles", "Chicago", "Houston", "Phoenix" ] } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "cities": [ "New York", "Los Angeles", "Chicago", "Houston", "Phoenix" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/cfp-financial-planner-directory-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "cities": [ "New York", "Los Angeles", "Chicago", "Houston", "Phoenix", ], } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/cfp-financial-planner-directory-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "cities": [ "New York", "Los Angeles", "Chicago", "Houston", "Phoenix" ] }' | apify call jungle_synthesizer/cfp-financial-planner-directory-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/cfp-financial-planner-directory-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "CFP Financial Planner Directory Scraper", "description": "Scrapes fee-only CERTIFIED FINANCIAL PLANNER® professionals from the NAPFA (National Association of Personal Financial Advisors) public directory. Returns advisor contact info, firm details, credentials, specialties, compensation model, and years of experience.", "version": "0.1", "x-build-id": "zm5mJ5u9dglvZMAIa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~cfp-financial-planner-directory-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-cfp-financial-planner-directory-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~cfp-financial-planner-directory-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-cfp-financial-planner-directory-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~cfp-financial-planner-directory-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-cfp-financial-planner-directory-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of advisors to return. Default is 10 for quick test runs.", "default": 10 }, "cities": { "title": "Cities to Search", "type": "array", "description": "List of US city names or zip codes to search. Each city search returns all NAPFA advisors near that location. Defaults to a curated list of ~60 major US cities covering all 50 states.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```