# Local Business Lead Finder for AI Agents (`iammienta/agent-local-business-icp-finder`) Actor Find local business lead candidates by category and location, then return structured records for AI agents and prospecting workflows: name, address, coordinates, website, phone clues, fit notes, source, and confidence. - **URL**: https://apify.com/iammienta/agent-local-business-icp-finder.md - **Developed by:** [Pete Mientkiewicz](https://apify.com/iammienta) (community) - **Categories:** AI, Agents, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Local Business Lead Finder for AI Agents Local Business Lead Finder for AI Agents finds local business lead candidates from a category and location, then returns structured records for prospecting, enrichment, and local-market research workflows. It is built for AI agents that need local business names, addresses, coordinates, website clues, phone clues, fit notes, source attribution, and confidence. ### Use cases - Find local business prospects by niche and geography. - Seed an AI lead-generation workflow with structured local records. - Build local market maps for dentists, gyms, solicitors, agencies, clinics, trades, and other categories. - Prepare a list for downstream website enrichment, email finding, or CRM review. - Compare local business density across towns or regions. ### Use this Actor when Use this Actor when an agent needs a small, structured set of local business candidates from a category and location. ### Do not use this Actor when Do not use it as a full Google Maps replacement, guaranteed contact database, or verified email/phone finder. It uses public local data sources and should be chained with enrichment tools. ### Input ```json { "category": "dentist", "location": "Portsmouth, UK", "maxResults": 5 } ```` ### Output The Actor writes one record per local business candidate to the default dataset. Typical fields include: - `name` - `category` - `location` - `displayAddress` - `latitude` - `longitude` - `website` - `phone` - `fitNotes` - `confidence` - `source` ### Agent workflow 1. Pass a business category and location. 2. Read local lead candidates from the default dataset. 3. Send records with websites to a website intelligence or lead scoring Actor. 4. Send records without websites to a manual review or additional discovery step. ### Limitations - Coverage depends on public local data availability. - Phone and website fields may be empty. - Results are lead candidates, not verified sales-ready contacts. ### Pricing and runtime This MVP is designed for small local prospecting batches. Keep `maxResults` modest for fast agent loops and use enrichment Actors for deeper contact discovery. # Actor input Schema ## `category` (type: `string`): Type of local business to find. ## `location` (type: `string`): Town, city, region, or country to search. ## `maxResults` (type: `integer`): Maximum local business records to return. ## Actor input object example ```json { "category": "dentist", "location": "Portsmouth, UK", "maxResults": 10 } ``` # Actor output Schema ## `results` (type: `string`): Structured results in the default dataset. # 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 = { "category": "dentist", "location": "Portsmouth, UK" }; // Run the Actor and wait for it to finish const run = await client.actor("iammienta/agent-local-business-icp-finder").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 = { "category": "dentist", "location": "Portsmouth, UK", } # Run the Actor and wait for it to finish run = client.actor("iammienta/agent-local-business-icp-finder").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 '{ "category": "dentist", "location": "Portsmouth, UK" }' | apify call iammienta/agent-local-business-icp-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=iammienta/agent-local-business-icp-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Local Business Lead Finder for AI Agents", "description": "Find local business lead candidates by category and location, then return structured records for AI agents and prospecting workflows: name, address, coordinates, website, phone clues, fit notes, source, and confidence.", "version": "0.1", "x-build-id": "cNt1LroUTnRuTdR5C" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/iammienta~agent-local-business-icp-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-iammienta-agent-local-business-icp-finder", "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/iammienta~agent-local-business-icp-finder/runs": { "post": { "operationId": "runs-sync-iammienta-agent-local-business-icp-finder", "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/iammienta~agent-local-business-icp-finder/run-sync": { "post": { "operationId": "run-sync-iammienta-agent-local-business-icp-finder", "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": [ "category", "location" ], "properties": { "category": { "title": "Business category", "type": "string", "description": "Type of local business to find." }, "location": { "title": "Location", "type": "string", "description": "Town, city, region, or country to search." }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 25, "type": "integer", "description": "Maximum local business records to return.", "default": 10 } } }, "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 } } } } } } } } } } ```